In view of the structure and action behavior of mechatronic systems,a method of searching fault propagation paths called maximum-probability path search(MPPS)is proposed,aiming to determine all possible failure propag...In view of the structure and action behavior of mechatronic systems,a method of searching fault propagation paths called maximum-probability path search(MPPS)is proposed,aiming to determine all possible failure propagation paths with their lengths if faults occur.First,the physical structure system,function behavior,and complex network theory are integrated to define a system structural-action network(SSAN).Second,based on the concept of SSAN,two properties of nodes and edges,i.e.,the topological property and reliability property,are combined to define the failure propagation property.Third,the proposed MPPS model provides all fault propagation paths and possible failure rates of nodes on these paths.Finally,numerical experiments have been implemented to show the accuracy and advancement compared with the methods of Function Space Iteration(FSI)and the algorithm of Ant Colony Optimization(ACO).展开更多
In order to meet the urgent need of infrared search and track applications for accurate identification and positioning of infrared guidance aircraft,an active-detection mid-wave infrared search and track system(ADMWIR...In order to meet the urgent need of infrared search and track applications for accurate identification and positioning of infrared guidance aircraft,an active-detection mid-wave infrared search and track system(ADMWIRSTS)based on"cat-eye effect"was developed.The ADMWIRSTS mainly consists of both a light beam control subsystem and an infrared search and track subsystem.The light beam control subsystem uses an integrated opto-mechanical two-dimensional pointing mirror to realize the control function of the azimuth and pitch directions of the system,which can cover the whole airspace range of 360°×90°.The infrared search and track subsystem uses two mid-wave infrared cooled 640×512 focal plane detectors for co-aperture beam expanding,infrared and illumination laser beam combining,infrared search,and two-stage track opto-mechanical design.In this work,the system integration design and structural finite-element analysis were conducted,the search imaging and two-stage track imaging for external scenes were performed,and the active-detection technologies were experimentally verified in the laboratory.The experimental investigation results show that the system can realize the infrared search and track imaging,and the accurate identification and positioning of the mid-wave infrared guidance,or infrared detection system through the echo of the illumination laser.The aforementioned work has important technical significance and practical application value for the development of compactly-integrated high-precision infrared search and track,and laser suppression system,and has broad application prospects in the protection of equipment,assets and infrastructures.展开更多
A hybrid carrier（HC） scheme based on weighted-type fractional Fourier transform（WFRFT） has been proposed recently.While most of the works focus on HC scheme＇s inherent characteristics, little attention is paid to...A hybrid carrier（HC） scheme based on weighted-type fractional Fourier transform（WFRFT） has been proposed recently.While most of the works focus on HC scheme＇s inherent characteristics, little attention is paid to the WFRFT modulation recognition.In this paper, a new theory is provided to recognize the WFRFT modulation based on higher order cumulants（HOC）. First, it is deduced that the optimal WFRFT received order can be obtained through the minimization of 4 th-order cumulants, C_（42）. Then, a combinatorial searching algorithm is designed to minimize C_（42）.Finally, simulation results show that the designed scheme has a high recognition rate and the combinatorial searching algorithm is effective and reliable.展开更多
The material distribution routing problem in the manufacturing system is a complex combinatorial optimization problem and its main task is to deliver materials to the working stations with low cost and high efficiency...The material distribution routing problem in the manufacturing system is a complex combinatorial optimization problem and its main task is to deliver materials to the working stations with low cost and high efficiency. A multi-objective model was presented for the material distribution routing problem in mixed manufacturing systems, and it was solved by a hybrid multi-objective evolutionary algorithm (HMOEA). The characteristics of the HMOEA are as follows: 1) A route pool is employed to preserve the best routes for the population initiation; 2) A specialized best?worst route crossover (BWRC) mode is designed to perform the crossover operators for selecting the best route from Chromosomes 1 to exchange with the worst one in Chromosomes 2, so that the better genes are inherited to the offspring; 3) A route swap mode is used to perform the mutation for improving the convergence speed and preserving the better gene; 4) Local heuristics search methods are applied in this algorithm. Computational study of a practical case shows that the proposed algorithm can decrease the total travel distance by 51.66%, enhance the average vehicle load rate by 37.85%, cut down 15 routes and reduce a deliver vehicle. The convergence speed of HMOEA is faster than that of famous NSGA-II.展开更多
On the basis of the theoretical analysis of a single-machine infinite-bus （SMIB）, using the modified linearized Phil- lips-Heffron model installed with unified power flow controller （UPFC）, the potential of the UP...On the basis of the theoretical analysis of a single-machine infinite-bus （SMIB）, using the modified linearized Phil- lips-Heffron model installed with unified power flow controller （UPFC）, the potential of the UPFC supplementary controller to enhance the dynamic stability of a power system is evaluated by measuring the electromechanical controllability through singular value decomposition （SVD） analysis. This controller is tuned to simultaneously shift the undamped electromeehanical modes to a prescribed zone in the s-plane. The problem of robust UPFC based damping controller is formulated as an optimization problem according to the eigenvalue-based multi-objective function comprising the damping factor, and the damping ratio of the undamped electromechanical modes to be solved using gravitational search algorithm （GSA） that has a strong ability to find the most optimistic results. The different loading conditions are simulated on a SMIB system and the rotor speed deviation, internal voltage deviation, DC voltage deviation and electrical power deviation responses are studied with the effect of this flexible AC transmission systems （FACTS） controller. The results reveal that the tuned GSA based UPFC controller using the proposed multi-objective function has an excellent capability in damping power system with low frequency oscillations and greatly enhances the dynamic stability of the power systems.展开更多
Cocrystallization integrates the merits of high energy and insensitivity between energetic molecules to obtain energetics with satisfying performance.However,how to obtain supramolecular synthons accurately and rapidl...Cocrystallization integrates the merits of high energy and insensitivity between energetic molecules to obtain energetics with satisfying performance.However,how to obtain supramolecular synthons accurately and rapidly for predicting the structure and property of cocrystal remains a challenging problem.In this research,an efficient systematic search approach to predict CL-20/2,4-DNI cocrystal has been proposed that 2,4-DNI revolves around CL-20 with a stoichiometric ratio of 1:1 in accordance with the specified rules(hydrogen bond length:2.2-3.0 Å;search radius:6.5 Å;the number of hydrogen bond:1-3).Eight possible supramolecular synthons were obtained by combining quantum chemistry with molecular mechanics.Crystal structure prediction indicated that there are four structures in cocrystal,namely P21/c,P212121,Pbca and Pna21,and CL-20/2,4-DNI cocrystal is likely to be P21/c and the corresponding cell parameters are Z=4,a=8.28 Å,b=12.17 Å,c=20.42 Å,α=90°,β=96.94°,γ=90°,and ρ=1.9353 g/cm^(3).To further study the intermolecular interaction of CL-20/2,4-DNI cocrystal,a series of theoretical analyses were employed including intermolecular interaction energy,electrostatic potential(ESP),Density of State(DOS),Hirshfeld surface analysis.The C-H…O hydrogen bonds are demonstrated as the predominant driving forces in the cocrystal formation.The mechanical properties and detonation properties of CL-20/2,4-DNI cocrystal implies that the cocrystal shows better ductility and excellent detonation performances(9257 m/s,39.27 GPa)and can serve as a promising energetic material.Cocrystal structure predicted was compared with the experimental one to verify the accuracy of systematic search approach.There is a less than 8.8%error between experiment and predict results,indicating the systematic search approach has extremely high reliability and accuracy.The systematic search approach can be a new strategy to search supramolecular synthons and identify structures effectively and does have the potential to promote the development of energetic cocrystal by theoretical design.展开更多
The jamming resource allocation problem of the aircraft formation cooperatively jamming netted radar system is investigated.An adaptive allocation strategy based on dynamic adaptive discrete cuckoo search algorithm(DA...The jamming resource allocation problem of the aircraft formation cooperatively jamming netted radar system is investigated.An adaptive allocation strategy based on dynamic adaptive discrete cuckoo search algorithm(DADCS)is proposed,whose core is to adjust allocation scheme of limited jamming resource of aircraft formation in real time to maintain the best jamming effectiveness against netted radar system.Firstly,considering the information fusion rules and different working modes of the netted radar system,a two-factor jamming effectiveness evaluation function is constructed,detection probability and aiming probability are adopted to characterize jamming effectiveness against netted radar system in searching and tracking mode,respectively.Then a nonconvex optimization model for cooperatively jamming netted radar system is established.Finally,a dynamic adaptive discrete cuckoo search algorithm(DADCS)is constructed by improving path update strategies and introducing a global learning mechanism,and a three-step solution method is proposed subsequently.Simulation results are provided to demonstrate the advantages of the proposed optimization strategy and the effectiveness of the improved algorithm.展开更多
To evaluate the credit risk of customers in power market precisely, the new chaotic searching and fuzzy neural network (FNN) hybrid algorithm were proposed. By combining with the chaotic searching, the learning abilit...To evaluate the credit risk of customers in power market precisely, the new chaotic searching and fuzzy neural network (FNN) hybrid algorithm were proposed. By combining with the chaotic searching, the learning ability of the FNN was markedly enhanced. Customers’ actual credit flaw data of power supply enterprises were collected to carry on the real evaluation, which can be treated as example for the model. The result shows that the proposed method surpasses the traditional statistical models in regard to the precision of forecasting and has a practical value. Compared with the results of ordinary FNN and ANN, the precision of the proposed algorithm can be enhanced by 2.2% and 4.5%, respectively.展开更多
LuGre model has been widely used in friction modeling and compensation.However,the new friction regime,named prestiction regime,cannot be accurately characterized by LuGre model in the latest research.With the extensi...LuGre model has been widely used in friction modeling and compensation.However,the new friction regime,named prestiction regime,cannot be accurately characterized by LuGre model in the latest research.With the extensive experimental observations of friction behaviors in the prestiction,some variables were abstracted to depict the rules in the prestiction regime.Based upon the knowledge of friction modeling,a novel friction model including the presliding regime,the gross sliding regime and the prestiction regime was then presented to overcome the shortcomings of the LuGre model.The reason that LuGre model cannot estimate the prestiction friction was analyzed in theory.Feasibility analysis of the proposed model in modeling the prestiction friction was also addressed.A parameter identification method for the proposed model based on multilevel coordinate search algorithm was presented.The proposed friction compensation strategy was composed of a nonlinear friction observer and a feedforward mechanism.The friction observer was designed to estimate the friction force in the presliding and the gross sliding regimes.And the friction force was estimated based on the model in the prestiction regime.The comparative trajectory tracking experiments were conducted on a simulator of inertially stabilization platforms among three control schemes:the single proportional–derivative(PD)control,the PD with LuGre model-based compensation and the PD with compensator based on the presented model.The experimental results reveal that the control scheme based on the proposed model has the best tracking performance.It reduces the peak-to-peak value(PPV)of tracking error to 0.2 mrad,which is improved almost 50%compared with the PD with LuGre model-based compensation.Compared to the single PD control,it reduces the PPV of error by 66.7%.展开更多
The current Grover quantum searching algorithm cannot identify the difference in importance of the search targets when it is applied to an unsorted quantum database, and the probability for each search target is equal...The current Grover quantum searching algorithm cannot identify the difference in importance of the search targets when it is applied to an unsorted quantum database, and the probability for each search target is equal. To solve this problem, a Grover searching algorithm based on weighted targets is proposed. First, each target is endowed a weight coefficient according to its importance. Applying these different weight coefficients, the targets are represented as quantum superposition states. Second, the novel Grover searching algorithm based on the quantum superposition of the weighted targets is constructed. Using this algorithm, the probability of getting each target can be approximated to the corresponding weight coefficient, which shows the flexibility of this algorithm. Finally, the validity of the algorithm is proved by a simple searching example.展开更多
A method for improving the level of reliability of distribution systems is presented by employing an integrated voltage sag mitigation method that comprises a two-staged strategy,namely,distribution network reconfigur...A method for improving the level of reliability of distribution systems is presented by employing an integrated voltage sag mitigation method that comprises a two-staged strategy,namely,distribution network reconfiguration(DNR)followed by DSTATCOM placement.Initially,an optimal DNR is applied to reduce the propagated voltage sags during the test period.The second stage involves optimal placement of the DSTATCOM to assist the already reconfigured network.The gravitational search algorithm is used in the process of optimal DNR and in placing DSTATCOM.Reliability assessment is performed using the well-known indices.The simulation results show that the proposed method is efficient and feasible for improving the level of system reliability.展开更多
Press & Publishing Journal (PPJ),March 6,1991:Upon PPJ edit-orial office's request,Institute of Scientific and Technological lnfor-mation of China (ISTTC) made a survey on the situation that how manytheses fro...Press & Publishing Journal (PPJ),March 6,1991:Upon PPJ edit-orial office's request,Institute of Scientific and Technological lnfor-mation of China (ISTTC) made a survey on the situation that how manytheses from China scientific and technological journals have been sele-cted by the 6 most important search systems (Science Literature Index,展开更多
An in-pixel histogramming time-to-digital converter(hTDC)based on octonary search and 4-tap phase detection is presented,aiming to improve frame rate while ensuring high precicion.The proposed hTDC is a 12-bit two-ste...An in-pixel histogramming time-to-digital converter(hTDC)based on octonary search and 4-tap phase detection is presented,aiming to improve frame rate while ensuring high precicion.The proposed hTDC is a 12-bit two-step converter consisting of a 6-bit coarse quantization and a 6-bit fine quantization,which supports a time resolution of 120 ps and multiphoton counting up to 2 GHz without a GHz reference frequency.The proposed hTDC is designed in 0.11μm CMOS process with an area consumption of 6900μm^(2).The data from a behavioral-level model is imported into the designed hTDC circuit for simulation verification.The post-simulation results show that the proposed hTDC achieves 0.8%depth precision in 9 m range for short-range system design specifications and 0.2%depth precision in 48 m range for long-range system design specifications.Under 30×10^(3) lux background light conditions,the proposed hTDC can be used for SPAD-based flash LiDAR sensor to achieve a frame rate to 40 fps with 200 ps resolution in 9 m range.展开更多
In this paper,a fusion model based on a long short-term memory(LSTM)neural network and enhanced search ant colony optimization(ENSACO)is proposed to predict the power degradation trend of proton exchange membrane fuel...In this paper,a fusion model based on a long short-term memory(LSTM)neural network and enhanced search ant colony optimization(ENSACO)is proposed to predict the power degradation trend of proton exchange membrane fuel cells(PEMFC).Firstly,the Shapley additive explanations(SHAP)value method is used to select external characteristic parameters with high contributions as inputs for the data-driven approach.Next,a novel swarm optimization algorithm,the enhanced search ant colony optimization,is proposed.This algorithm improves the ant colony optimization(ACO)algorithm based on a reinforcement factor to avoid premature convergence and accelerate the convergence speed.Comparative experiments are set up to compare the performance differences between particle swarm optimization(PSO),ACO,and ENSACO.Finally,a data-driven method based on ENSACO-LSTM is proposed to predict the power degradation trend of PEMFCs.And actual aging data is used to validate the method.The results show that,within a limited number of iterations,the optimization capability of ENSACO is significantly stronger than that of PSO and ACO.Additionally,the prediction accuracy of the ENSACO-LSTM method is greatly improved,with an average increase of approximately 50.58%compared to LSTM,PSO-LSTM,and ACO-LSTM.展开更多
As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in mult...As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in multi-trip and multi-drop(VRP-mmD).The problem aims at making schedules for the trucks and drones such that the total travel time is minimized.This paper formulate the problem with a mixed integer program-ming model and propose a two-phase algorithm,i.e.,a parallel route construction heuristic(PRCH)for the first phase and an adaptive neighbor searching heuristic(ANSH)for the second phase.The PRCH generates an initial solution by con-currently assigning as many nodes as possible to the truck–drone pair to progressively reduce the waiting time at the rendezvous node in the first phase.Then the ANSH improves the initial solution by adaptively exploring the neighborhoods in the second phase.Numerical tests on some benchmark data are conducted to verify the performance of the algorithm.The results show that the proposed algorithm can found better solu-tions than some state-of-the-art methods for all instances.More-over,an extensive analysis highlights the stability of the pro-posed algorithm.展开更多
System upgrades in unmanned systems have made Unmanned Aerial Vehicle(UAV)-based patrolling and monitoring a preferred solution for ocean surveillance.However,dynamic environments and large-scale deployments pose sign...System upgrades in unmanned systems have made Unmanned Aerial Vehicle(UAV)-based patrolling and monitoring a preferred solution for ocean surveillance.However,dynamic environments and large-scale deployments pose significant challenges for efficient decision-making,necessitating a modular multiagent control system.Deep Reinforcement Learning(DRL)and Decision Tree(DT)have been utilized for these complex decision-making tasks,but each has its limitations:DRL is highly adaptive but lacks interpretability,while DT is inherently interpretable but has limited adaptability.To overcome these challenges,we propose the Adaptive Interpretable Decision Tree(AIDT),an evolutionary-based algorithm that is both adaptable to diverse environmental settings and highly interpretable in its decision-making processes.We first construct a Markov decision process(MDP)-based simulation environment using the Cooperative Submarine Search task as a representative scenario for training and testing the proposed method.Specifically,we use the heat map as a state variable to address the issue of multi-agent input state proliferation.Next,we introduce the curiosity-guiding intrinsic reward to encourage comprehensive exploration and enhance algorithm performance.Additionally,we incorporate decision tree size as an influence factor in the adaptation process to balance task completion with computational efficiency.To further improve the generalization capability of the decision tree,we apply a normalization method to ensure consistent processing of input states.Finally,we validate the proposed algorithm in different environmental settings,and the results demonstrate both its adaptability and interpretability.展开更多
International freedom of the air(traffic rights)is a key resource for airlines to carry out international air transport business.An efficient and reasonable traffic right resource allocation within a country between a...International freedom of the air(traffic rights)is a key resource for airlines to carry out international air transport business.An efficient and reasonable traffic right resource allocation within a country between airlines can affect the quality of a country’s participation in international air transport.In this paper,a multi-objective mixed-integer programming model for traffic rights resource allocation is developed to minimize passenger travel mileages and maximize the number of traffic rights resources allocated to hub airports and competitive carriers.A hybrid heuristic algorithm combining the genetic algorithm and the variable neighborhood search is devised to solve the model.The results show that the optimal allocation scheme aligns with the principle of fairness,indicating that the proposed model can play a certain guiding role in and provide an innovative perspective on traffic rights resource allocation in various countries.展开更多
With the rapid development of low-altitude economy and unmanned aerial vehicles (UAVs) deployment technology, aerial-ground collaborative delivery (AGCD) is emerging as a novel mode of last-mile delivery, where the ve...With the rapid development of low-altitude economy and unmanned aerial vehicles (UAVs) deployment technology, aerial-ground collaborative delivery (AGCD) is emerging as a novel mode of last-mile delivery, where the vehicle and its onboard UAVs are utilized efficiently. Vehicles not only provide delivery services to customers but also function as mobile ware-houses and launch/recovery platforms for UAVs. This paper addresses the vehicle routing problem with UAVs considering time window and UAV multi-delivery (VRPU-TW&MD). A mixed integer linear programming (MILP) model is developed to mini-mize delivery costs while incorporating constraints related to UAV energy consumption. Subsequently, a micro-evolution aug-mented large neighborhood search (MEALNS) algorithm incor-porating adaptive large neighborhood search (ALNS) and micro-evolution mechanism is proposed. Numerical experiments demonstrate the effectiveness of both the model and algorithm in solving the VRPU-TW&MD. The impact of key parameters on delivery performance is explored by sensitivity analysis.展开更多
Fog computing has emerged as an important technology which can improve the performance of computation-intensive and latency-critical communication networks.Nevertheless,the fog computing Internet-of-Things(IoT)systems...Fog computing has emerged as an important technology which can improve the performance of computation-intensive and latency-critical communication networks.Nevertheless,the fog computing Internet-of-Things(IoT)systems are susceptible to malicious eavesdropping attacks during the information transmission,and this issue has not been adequately addressed.In this paper,we propose a physical-layer secure fog computing IoT system model,which is able to improve the physical layer security of fog computing IoT networks against the malicious eavesdropping of multiple eavesdroppers.The secrecy rate of the proposed model is analyzed,and the quantum galaxy–based search algorithm(QGSA)is proposed to solve the hybrid task scheduling and resource management problem of the network.The computational complexity and convergence of the proposed algorithm are analyzed.Simulation results validate the efficiency of the proposed model and reveal the influence of various environmental parameters on fog computing IoT networks.Moreover,the simulation results demonstrate that the proposed hybrid task scheduling and resource management scheme can effectively enhance secrecy performance across different communication scenarios.展开更多
The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a nove...The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.展开更多
基金Project(2017JBZ103)supported by the Fundamental Research Funds for the Central Universities,China
文摘In view of the structure and action behavior of mechatronic systems,a method of searching fault propagation paths called maximum-probability path search(MPPS)is proposed,aiming to determine all possible failure propagation paths with their lengths if faults occur.First,the physical structure system,function behavior,and complex network theory are integrated to define a system structural-action network(SSAN).Second,based on the concept of SSAN,two properties of nodes and edges,i.e.,the topological property and reliability property,are combined to define the failure propagation property.Third,the proposed MPPS model provides all fault propagation paths and possible failure rates of nodes on these paths.Finally,numerical experiments have been implemented to show the accuracy and advancement compared with the methods of Function Space Iteration(FSI)and the algorithm of Ant Colony Optimization(ACO).
基金Supported by the Fundamental Scientific Research Plan of China(JCKY2021130B033)。
文摘In order to meet the urgent need of infrared search and track applications for accurate identification and positioning of infrared guidance aircraft,an active-detection mid-wave infrared search and track system(ADMWIRSTS)based on"cat-eye effect"was developed.The ADMWIRSTS mainly consists of both a light beam control subsystem and an infrared search and track subsystem.The light beam control subsystem uses an integrated opto-mechanical two-dimensional pointing mirror to realize the control function of the azimuth and pitch directions of the system,which can cover the whole airspace range of 360°×90°.The infrared search and track subsystem uses two mid-wave infrared cooled 640×512 focal plane detectors for co-aperture beam expanding,infrared and illumination laser beam combining,infrared search,and two-stage track opto-mechanical design.In this work,the system integration design and structural finite-element analysis were conducted,the search imaging and two-stage track imaging for external scenes were performed,and the active-detection technologies were experimentally verified in the laboratory.The experimental investigation results show that the system can realize the infrared search and track imaging,and the accurate identification and positioning of the mid-wave infrared guidance,or infrared detection system through the echo of the illumination laser.The aforementioned work has important technical significance and practical application value for the development of compactly-integrated high-precision infrared search and track,and laser suppression system,and has broad application prospects in the protection of equipment,assets and infrastructures.
基金supported by the National Natural Science Foundation of China(6127125061571460)
文摘A hybrid carrier（HC） scheme based on weighted-type fractional Fourier transform（WFRFT） has been proposed recently.While most of the works focus on HC scheme＇s inherent characteristics, little attention is paid to the WFRFT modulation recognition.In this paper, a new theory is provided to recognize the WFRFT modulation based on higher order cumulants（HOC）. First, it is deduced that the optimal WFRFT received order can be obtained through the minimization of 4 th-order cumulants, C_（42）. Then, a combinatorial searching algorithm is designed to minimize C_（42）.Finally, simulation results show that the designed scheme has a high recognition rate and the combinatorial searching algorithm is effective and reliable.
基金Project(50775089)supported by the National Natural Science Foundation of ChinaProject(2007AA04Z190,2009AA043301)supported by the National High Technology Research and Development Program of ChinaProject(2005CB724100)supported by the National Basic Research Program of China
文摘The material distribution routing problem in the manufacturing system is a complex combinatorial optimization problem and its main task is to deliver materials to the working stations with low cost and high efficiency. A multi-objective model was presented for the material distribution routing problem in mixed manufacturing systems, and it was solved by a hybrid multi-objective evolutionary algorithm (HMOEA). The characteristics of the HMOEA are as follows: 1) A route pool is employed to preserve the best routes for the population initiation; 2) A specialized best?worst route crossover (BWRC) mode is designed to perform the crossover operators for selecting the best route from Chromosomes 1 to exchange with the worst one in Chromosomes 2, so that the better genes are inherited to the offspring; 3) A route swap mode is used to perform the mutation for improving the convergence speed and preserving the better gene; 4) Local heuristics search methods are applied in this algorithm. Computational study of a practical case shows that the proposed algorithm can decrease the total travel distance by 51.66%, enhance the average vehicle load rate by 37.85%, cut down 15 routes and reduce a deliver vehicle. The convergence speed of HMOEA is faster than that of famous NSGA-II.
文摘On the basis of the theoretical analysis of a single-machine infinite-bus （SMIB）, using the modified linearized Phil- lips-Heffron model installed with unified power flow controller （UPFC）, the potential of the UPFC supplementary controller to enhance the dynamic stability of a power system is evaluated by measuring the electromechanical controllability through singular value decomposition （SVD） analysis. This controller is tuned to simultaneously shift the undamped electromeehanical modes to a prescribed zone in the s-plane. The problem of robust UPFC based damping controller is formulated as an optimization problem according to the eigenvalue-based multi-objective function comprising the damping factor, and the damping ratio of the undamped electromechanical modes to be solved using gravitational search algorithm （GSA） that has a strong ability to find the most optimistic results. The different loading conditions are simulated on a SMIB system and the rotor speed deviation, internal voltage deviation, DC voltage deviation and electrical power deviation responses are studied with the effect of this flexible AC transmission systems （FACTS） controller. The results reveal that the tuned GSA based UPFC controller using the proposed multi-objective function has an excellent capability in damping power system with low frequency oscillations and greatly enhances the dynamic stability of the power systems.
基金the support of the National Natural Science Foundation of China(No.22005090)Beijing Institute of Technology Research Fund Program for Young Scholars+2 种基金the National Natural Science Foundation of China(No.11672040 and No.21801016)Open Research Fund Program of Science and Technology on Aerospace Chemical Power Laboratory(STACPL120201B02)the State Key Laboratory of Explosion Science and Technology(No.YB2016-17)。
文摘Cocrystallization integrates the merits of high energy and insensitivity between energetic molecules to obtain energetics with satisfying performance.However,how to obtain supramolecular synthons accurately and rapidly for predicting the structure and property of cocrystal remains a challenging problem.In this research,an efficient systematic search approach to predict CL-20/2,4-DNI cocrystal has been proposed that 2,4-DNI revolves around CL-20 with a stoichiometric ratio of 1:1 in accordance with the specified rules(hydrogen bond length:2.2-3.0 Å;search radius:6.5 Å;the number of hydrogen bond:1-3).Eight possible supramolecular synthons were obtained by combining quantum chemistry with molecular mechanics.Crystal structure prediction indicated that there are four structures in cocrystal,namely P21/c,P212121,Pbca and Pna21,and CL-20/2,4-DNI cocrystal is likely to be P21/c and the corresponding cell parameters are Z=4,a=8.28 Å,b=12.17 Å,c=20.42 Å,α=90°,β=96.94°,γ=90°,and ρ=1.9353 g/cm^(3).To further study the intermolecular interaction of CL-20/2,4-DNI cocrystal,a series of theoretical analyses were employed including intermolecular interaction energy,electrostatic potential(ESP),Density of State(DOS),Hirshfeld surface analysis.The C-H…O hydrogen bonds are demonstrated as the predominant driving forces in the cocrystal formation.The mechanical properties and detonation properties of CL-20/2,4-DNI cocrystal implies that the cocrystal shows better ductility and excellent detonation performances(9257 m/s,39.27 GPa)and can serve as a promising energetic material.Cocrystal structure predicted was compared with the experimental one to verify the accuracy of systematic search approach.There is a less than 8.8%error between experiment and predict results,indicating the systematic search approach has extremely high reliability and accuracy.The systematic search approach can be a new strategy to search supramolecular synthons and identify structures effectively and does have the potential to promote the development of energetic cocrystal by theoretical design.
文摘The jamming resource allocation problem of the aircraft formation cooperatively jamming netted radar system is investigated.An adaptive allocation strategy based on dynamic adaptive discrete cuckoo search algorithm(DADCS)is proposed,whose core is to adjust allocation scheme of limited jamming resource of aircraft formation in real time to maintain the best jamming effectiveness against netted radar system.Firstly,considering the information fusion rules and different working modes of the netted radar system,a two-factor jamming effectiveness evaluation function is constructed,detection probability and aiming probability are adopted to characterize jamming effectiveness against netted radar system in searching and tracking mode,respectively.Then a nonconvex optimization model for cooperatively jamming netted radar system is established.Finally,a dynamic adaptive discrete cuckoo search algorithm(DADCS)is constructed by improving path update strategies and introducing a global learning mechanism,and a three-step solution method is proposed subsequently.Simulation results are provided to demonstrate the advantages of the proposed optimization strategy and the effectiveness of the improved algorithm.
基金Project(50579101) supported by the National Natural Science Foundation of China
文摘To evaluate the credit risk of customers in power market precisely, the new chaotic searching and fuzzy neural network (FNN) hybrid algorithm were proposed. By combining with the chaotic searching, the learning ability of the FNN was markedly enhanced. Customers’ actual credit flaw data of power supply enterprises were collected to carry on the real evaluation, which can be treated as example for the model. The result shows that the proposed method surpasses the traditional statistical models in regard to the precision of forecasting and has a practical value. Compared with the results of ordinary FNN and ANN, the precision of the proposed algorithm can be enhanced by 2.2% and 4.5%, respectively.
基金Projects(51135009,51105371) supported by the National Natural Science Foundation of China
文摘LuGre model has been widely used in friction modeling and compensation.However,the new friction regime,named prestiction regime,cannot be accurately characterized by LuGre model in the latest research.With the extensive experimental observations of friction behaviors in the prestiction,some variables were abstracted to depict the rules in the prestiction regime.Based upon the knowledge of friction modeling,a novel friction model including the presliding regime,the gross sliding regime and the prestiction regime was then presented to overcome the shortcomings of the LuGre model.The reason that LuGre model cannot estimate the prestiction friction was analyzed in theory.Feasibility analysis of the proposed model in modeling the prestiction friction was also addressed.A parameter identification method for the proposed model based on multilevel coordinate search algorithm was presented.The proposed friction compensation strategy was composed of a nonlinear friction observer and a feedforward mechanism.The friction observer was designed to estimate the friction force in the presliding and the gross sliding regimes.And the friction force was estimated based on the model in the prestiction regime.The comparative trajectory tracking experiments were conducted on a simulator of inertially stabilization platforms among three control schemes:the single proportional–derivative(PD)control,the PD with LuGre model-based compensation and the PD with compensator based on the presented model.The experimental results reveal that the control scheme based on the proposed model has the best tracking performance.It reduces the peak-to-peak value(PPV)of tracking error to 0.2 mrad,which is improved almost 50%compared with the PD with LuGre model-based compensation.Compared to the single PD control,it reduces the PPV of error by 66.7%.
基金the National Natural Science Foundation of China (60773065).
文摘The current Grover quantum searching algorithm cannot identify the difference in importance of the search targets when it is applied to an unsorted quantum database, and the probability for each search target is equal. To solve this problem, a Grover searching algorithm based on weighted targets is proposed. First, each target is endowed a weight coefficient according to its importance. Applying these different weight coefficients, the targets are represented as quantum superposition states. Second, the novel Grover searching algorithm based on the quantum superposition of the weighted targets is constructed. Using this algorithm, the probability of getting each target can be approximated to the corresponding weight coefficient, which shows the flexibility of this algorithm. Finally, the validity of the algorithm is proved by a simple searching example.
基金Project(DIP-2012-30)supported by the Universiti Kebangsaan,Malaysia
文摘A method for improving the level of reliability of distribution systems is presented by employing an integrated voltage sag mitigation method that comprises a two-staged strategy,namely,distribution network reconfiguration(DNR)followed by DSTATCOM placement.Initially,an optimal DNR is applied to reduce the propagated voltage sags during the test period.The second stage involves optimal placement of the DSTATCOM to assist the already reconfigured network.The gravitational search algorithm is used in the process of optimal DNR and in placing DSTATCOM.Reliability assessment is performed using the well-known indices.The simulation results show that the proposed method is efficient and feasible for improving the level of system reliability.
文摘Press & Publishing Journal (PPJ),March 6,1991:Upon PPJ edit-orial office's request,Institute of Scientific and Technological lnfor-mation of China (ISTTC) made a survey on the situation that how manytheses from China scientific and technological journals have been sele-cted by the 6 most important search systems (Science Literature Index,
基金National Key Research and Development Program of China(2022YFB2804401)。
文摘An in-pixel histogramming time-to-digital converter(hTDC)based on octonary search and 4-tap phase detection is presented,aiming to improve frame rate while ensuring high precicion.The proposed hTDC is a 12-bit two-step converter consisting of a 6-bit coarse quantization and a 6-bit fine quantization,which supports a time resolution of 120 ps and multiphoton counting up to 2 GHz without a GHz reference frequency.The proposed hTDC is designed in 0.11μm CMOS process with an area consumption of 6900μm^(2).The data from a behavioral-level model is imported into the designed hTDC circuit for simulation verification.The post-simulation results show that the proposed hTDC achieves 0.8%depth precision in 9 m range for short-range system design specifications and 0.2%depth precision in 48 m range for long-range system design specifications.Under 30×10^(3) lux background light conditions,the proposed hTDC can be used for SPAD-based flash LiDAR sensor to achieve a frame rate to 40 fps with 200 ps resolution in 9 m range.
基金Supported by the Major Science and Technology Project of Jilin Province(20220301010GX)the International Scientific and Technological Cooperation(20240402071GH).
文摘In this paper,a fusion model based on a long short-term memory(LSTM)neural network and enhanced search ant colony optimization(ENSACO)is proposed to predict the power degradation trend of proton exchange membrane fuel cells(PEMFC).Firstly,the Shapley additive explanations(SHAP)value method is used to select external characteristic parameters with high contributions as inputs for the data-driven approach.Next,a novel swarm optimization algorithm,the enhanced search ant colony optimization,is proposed.This algorithm improves the ant colony optimization(ACO)algorithm based on a reinforcement factor to avoid premature convergence and accelerate the convergence speed.Comparative experiments are set up to compare the performance differences between particle swarm optimization(PSO),ACO,and ENSACO.Finally,a data-driven method based on ENSACO-LSTM is proposed to predict the power degradation trend of PEMFCs.And actual aging data is used to validate the method.The results show that,within a limited number of iterations,the optimization capability of ENSACO is significantly stronger than that of PSO and ACO.Additionally,the prediction accuracy of the ENSACO-LSTM method is greatly improved,with an average increase of approximately 50.58%compared to LSTM,PSO-LSTM,and ACO-LSTM.
文摘As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in multi-trip and multi-drop(VRP-mmD).The problem aims at making schedules for the trucks and drones such that the total travel time is minimized.This paper formulate the problem with a mixed integer program-ming model and propose a two-phase algorithm,i.e.,a parallel route construction heuristic(PRCH)for the first phase and an adaptive neighbor searching heuristic(ANSH)for the second phase.The PRCH generates an initial solution by con-currently assigning as many nodes as possible to the truck–drone pair to progressively reduce the waiting time at the rendezvous node in the first phase.Then the ANSH improves the initial solution by adaptively exploring the neighborhoods in the second phase.Numerical tests on some benchmark data are conducted to verify the performance of the algorithm.The results show that the proposed algorithm can found better solu-tions than some state-of-the-art methods for all instances.More-over,an extensive analysis highlights the stability of the pro-posed algorithm.
文摘System upgrades in unmanned systems have made Unmanned Aerial Vehicle(UAV)-based patrolling and monitoring a preferred solution for ocean surveillance.However,dynamic environments and large-scale deployments pose significant challenges for efficient decision-making,necessitating a modular multiagent control system.Deep Reinforcement Learning(DRL)and Decision Tree(DT)have been utilized for these complex decision-making tasks,but each has its limitations:DRL is highly adaptive but lacks interpretability,while DT is inherently interpretable but has limited adaptability.To overcome these challenges,we propose the Adaptive Interpretable Decision Tree(AIDT),an evolutionary-based algorithm that is both adaptable to diverse environmental settings and highly interpretable in its decision-making processes.We first construct a Markov decision process(MDP)-based simulation environment using the Cooperative Submarine Search task as a representative scenario for training and testing the proposed method.Specifically,we use the heat map as a state variable to address the issue of multi-agent input state proliferation.Next,we introduce the curiosity-guiding intrinsic reward to encourage comprehensive exploration and enhance algorithm performance.Additionally,we incorporate decision tree size as an influence factor in the adaptation process to balance task completion with computational efficiency.To further improve the generalization capability of the decision tree,we apply a normalization method to ensure consistent processing of input states.Finally,we validate the proposed algorithm in different environmental settings,and the results demonstrate both its adaptability and interpretability.
基金supported by the National Natural Science Foundation of Chinathe Civil Aviation Administration of China (U2333206).
文摘International freedom of the air(traffic rights)is a key resource for airlines to carry out international air transport business.An efficient and reasonable traffic right resource allocation within a country between airlines can affect the quality of a country’s participation in international air transport.In this paper,a multi-objective mixed-integer programming model for traffic rights resource allocation is developed to minimize passenger travel mileages and maximize the number of traffic rights resources allocated to hub airports and competitive carriers.A hybrid heuristic algorithm combining the genetic algorithm and the variable neighborhood search is devised to solve the model.The results show that the optimal allocation scheme aligns with the principle of fairness,indicating that the proposed model can play a certain guiding role in and provide an innovative perspective on traffic rights resource allocation in various countries.
基金supported by the Fundamental Research Funds for the Central Universities(2024JBZX038)the National Natural Science Foundation of China(62076023).
文摘With the rapid development of low-altitude economy and unmanned aerial vehicles (UAVs) deployment technology, aerial-ground collaborative delivery (AGCD) is emerging as a novel mode of last-mile delivery, where the vehicle and its onboard UAVs are utilized efficiently. Vehicles not only provide delivery services to customers but also function as mobile ware-houses and launch/recovery platforms for UAVs. This paper addresses the vehicle routing problem with UAVs considering time window and UAV multi-delivery (VRPU-TW&MD). A mixed integer linear programming (MILP) model is developed to mini-mize delivery costs while incorporating constraints related to UAV energy consumption. Subsequently, a micro-evolution aug-mented large neighborhood search (MEALNS) algorithm incor-porating adaptive large neighborhood search (ALNS) and micro-evolution mechanism is proposed. Numerical experiments demonstrate the effectiveness of both the model and algorithm in solving the VRPU-TW&MD. The impact of key parameters on delivery performance is explored by sensitivity analysis.
基金supported by the National Natural Science Foundation of China(61571149,62001139)the Initiation Fund for Postdoctoral Research in Heilongjiang Province(LBH-Q19098)the Natural Science Foundation of Heilongjiang Province(LH2020F0178).
文摘Fog computing has emerged as an important technology which can improve the performance of computation-intensive and latency-critical communication networks.Nevertheless,the fog computing Internet-of-Things(IoT)systems are susceptible to malicious eavesdropping attacks during the information transmission,and this issue has not been adequately addressed.In this paper,we propose a physical-layer secure fog computing IoT system model,which is able to improve the physical layer security of fog computing IoT networks against the malicious eavesdropping of multiple eavesdroppers.The secrecy rate of the proposed model is analyzed,and the quantum galaxy–based search algorithm(QGSA)is proposed to solve the hybrid task scheduling and resource management problem of the network.The computational complexity and convergence of the proposed algorithm are analyzed.Simulation results validate the efficiency of the proposed model and reveal the influence of various environmental parameters on fog computing IoT networks.Moreover,the simulation results demonstrate that the proposed hybrid task scheduling and resource management scheme can effectively enhance secrecy performance across different communication scenarios.
基金Fundamental Research Funds for the Central Universities(2024JBZX038)National Natural Science F oundation of China(62076023)。
文摘The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.
