In the present study,molecular dynamic simulation(MD)was used to investigate the plastic deformation process of the Fe-Mn alloys with different Mn contents.The influences of Mn contents ranging from 10%to 30%(at%)on t...In the present study,molecular dynamic simulation(MD)was used to investigate the plastic deformation process of the Fe-Mn alloys with different Mn contents.The influences of Mn contents ranging from 10%to 30%(at%)on the deformation behavior and the controlling mechanism of the Fe-base alloys were analyzed.The results show that phase transformations and{112}<111>_(BCC)deformation twinning occur in all Fe-Mn alloys but follow different deformation paths.In the Fe-10%Mn alloy the deformation twinning mechanism obeys the FCC-related path,the Fe-20%Mn alloy involves both the FCC-and HCP-related paths,and the deformation of the Fe-30%Mn alloy is dominated by the HCP-related twinning path.The addition of Mn can increase the stacking fault energy and retard the activation of slip systems as well as the formation of stacking faults.Thus,a higher content of Mn can delay the FCC®ε-martensite and the subsequentε-martensite®BCC phase transition at the intersection of twoε-martensitic bands.Therefore,the addition of Mn alloying element increases the yield strength and reduces the elastic modulus of the Fe-Mn alloys.The formation of deformation twins will contribute to the work-hardening effect and delay the necking and fracture of alloys.It is expected that the results in the present study will provide theoretical reference for the design and optimization of high-performance steels.展开更多
An effective algorithm based on signal coverage of effective communication and local energy-consumption saving strategy is proposed for the application in wireless sensor networks.This algorithm consists of two sub-al...An effective algorithm based on signal coverage of effective communication and local energy-consumption saving strategy is proposed for the application in wireless sensor networks.This algorithm consists of two sub-algorithms.One is the multi-hop partition subspaces clustering algorithm for ensuring local energybalanced consumption ascribed to the deployment from another algorithm of distributed locating deployment based on efficient communication coverage probability（DLD-ECCP）.DLD-ECCP makes use of the characteristics of Markov chain and probabilistic optimization to obtain the optimum topology and number of sensor nodes.Through simulation,the relative data demonstrate the advantages of the proposed approaches on saving hardware resources and energy consumption of networks.展开更多
Focused on the Klinkenberg effect on gas seepage, the independently developed triaxial experimental system of gas seepage was applied to conduct research on the seepage characteristics of coal seam gas. By means of ex...Focused on the Klinkenberg effect on gas seepage, the independently developed triaxial experimental system of gas seepage was applied to conduct research on the seepage characteristics of coal seam gas. By means of experimental data analysis and theoretical derivation, a calculation method of coal seam gas permeability was proposed, which synthesized the respective influences of gas dynamic viscosity, compressibility factor and Klinkenberg effect. The study results show that the Klinkenberg effect has a significant influence on the coal seam gas seepage, the permeability estimated with the method considering the Klinkenberg effect is correct, and this permeability can fully reflect the true seepage state of the gas. For the gas around the standard conditions, the influences of dynamic viscosity and compressibility factor on the permeability may be ignored. For the gas deviating far away from the standard conditions, the influences of dynamic viscosity and compressibility factor on the permeability must be considered. The research results have certain guiding significance in forming a correct understanding of the Klinkenberg effect and selecting a more accurate calculation method for the permeability of coal containing gas.展开更多
Visual background extraction algorithm(ViBe)uses the first frame image to initialize the background model,which can easily introduce the“ghost”.Because ViBe uses the fixed segmentation threshold to achieve the foreg...Visual background extraction algorithm(ViBe)uses the first frame image to initialize the background model,which can easily introduce the“ghost”.Because ViBe uses the fixed segmentation threshold to achieve the foreground and background segmentation,the detection results in many false detections for the highly dynamic background.To solve these problems,an improved ghost suppression and adaptive Visual Background Extraction algorithm is proposed in this paper.Firstly,with the pixel’s temporal and spatial information,the historical pixels of a certain combination are used to initialize the background model in the odd frames of the video sequence.Secondly,the background sample set combined with the neighborhood pixels are used to determine a complex degree of the background,to acquire the adaptive segmentation threshold.Thirdly,the update rate is adjusted based on the complexity of the background.Finally,the detected result goes through a post-processing to achieve better detection results.The experimental results show that the improved algorithm will not only quickly suppress the“ghost”,but also have a better detection in a complex dynamic background.展开更多
The trustworthiness analysis and evaluation are the bases of the trust chain transfer. In this paper the formal method of trustworthiness analysis of a system based on the noninterfer- ence （NI） theory of the inform...The trustworthiness analysis and evaluation are the bases of the trust chain transfer. In this paper the formal method of trustworthiness analysis of a system based on the noninterfer- ence （NI） theory of the information flow is studied. Firstly, existing methods cannot analyze the impact of the system states on the trustworthiness of software during the process of trust chain trans- fer. To solve this problem, the impact of the system state on trust- worthiness of software is investigated, the run-time mutual interfer- ence behavior of software entitles is described and an interference model of the access control automaton of a system is established. Secondly, based on the intransitive noninterference （INI） theory, a formal analytic method of trustworthiness for trust chain transfer is proposed, providing a theoretical basis for the analysis of dynamic trustworthiness of software during the trust chain transfer process. Thirdly, a prototype system with dynamic trustworthiness on a plat- form with dual core architecture is constructed and a verification algorithm of the system trustworthiness is provided. Finally, the monitor hypothesis is extended to the dynamic monitor hypothe- sis, a theorem of static judgment rule of system trustworthiness is provided, which is useful to prove dynamic trustworthiness of a system at the beginning of system construction. Compared with previous work in this field, this research proposes not only a formal analytic method for the determination of system trustworthiness, but also a modeling method and an analysis algorithm that are feasible for practical implementation.展开更多
To accelerate the selection process of feature subsets in the rough set theory （RST）, an ensemble elitist roles based quantum game （EERQG） algorithm is proposed for feature selec- tion. Firstly, the multilevel eli...To accelerate the selection process of feature subsets in the rough set theory （RST）, an ensemble elitist roles based quantum game （EERQG） algorithm is proposed for feature selec- tion. Firstly, the multilevel elitist roles based dynamics equilibrium strategy is established, and both immigration and emigration of elitists are able to be self-adaptive to balance between exploration and exploitation for feature selection. Secondly, the utility matrix of trust margins is introduced to the model of multilevel elitist roles to enhance various elitist roles＇ performance of searching the optimal feature subsets, and the win-win utility solutions for feature selec- tion can be attained. Meanwhile, a novel ensemble quantum game strategy is designed as an intriguing exhibiting structure to perfect the dynamics equilibrium of multilevel elitist roles. Finally, the en- semble manner of multilevel elitist roles is employed to achieve the global minimal feature subset, which will greatly improve the fea- sibility and effectiveness. Experiment results show the proposed EERQG algorithm has superiority compared to the existing feature selection algorithms.展开更多
As a typical industrial Internet of things(IIOT)service,demand response(DR)is becoming a promising enabler for intelligent energy management in 6 G-enabled smart grid systems,to achieve quick response for supply-deman...As a typical industrial Internet of things(IIOT)service,demand response(DR)is becoming a promising enabler for intelligent energy management in 6 G-enabled smart grid systems,to achieve quick response for supply-demand mismatches.How-ever,existing literatures try to adjust customers’load profiles optimally,instead of electricity overhead,energy consumption patterns of residential appliances,customer satisfaction levels,and energy consumption habits.In this paper,a novel DR method is investigated by mixing the aforementioned factors,where the residential customer cluster is proposed to enhance the performance.Clustering approaches are leveraged to study the electricity consumption habits of various customers by extracting their features and characteristics from historical data.Based on the extracted information,the residential appliances can be scheduled effectively and flexibly.Moreover,we propose and study an efficient optimization framework to obtain the optimal scheduling solution by using clustering and deep learning methods.Extensive simulation experiments are conducted with real-world traces.Numerical results show that the proposed DR method and optimization framework outperform other baseline schemes in terms of the system overhead and peak-to-average ratio(PAR).The impact of various factors on the system utility is further analyzed,which provides useful insights on improving the efficiency of the DR strategy.With the achievement of efficient and intelligent energy management,the proposed method also promotes the realization of China’s carbon peaking and carbon neutrality goals.展开更多
Particle swarm optimization （PSO） is a new heuristic algorithm which has been applied to many optimization problems successfully. Attribute reduction is a key studying point of the rough set theory, and it has been ...Particle swarm optimization （PSO） is a new heuristic algorithm which has been applied to many optimization problems successfully. Attribute reduction is a key studying point of the rough set theory, and it has been proven that computing minimal reduc- tion of decision tables is a non-derterministic polynomial （NP）-hard problem. A new cooperative extended attribute reduction algorithm named Co-PSAR based on improved PSO is proposed, in which the cooperative evolutionary strategy with suitable fitness func- tions is involved to learn a good hypothesis for accelerating the optimization of searching minimal attribute reduction. Experiments on Benchmark functions and University of California, Irvine （UCI） data sets, compared with other algorithms, verify the superiority of the Co-PSAR algorithm in terms of the convergence speed, efficiency and accuracy for the attribute reduction.展开更多
Cooperative jamming weapon-target assignment （CJWTA） problem is a key issue in electronic countermeasures （ECM）. Some symbols which relevant to the CJWTA are defined firstly. Then, a formulation of jamming fitness...Cooperative jamming weapon-target assignment （CJWTA） problem is a key issue in electronic countermeasures （ECM）. Some symbols which relevant to the CJWTA are defined firstly. Then, a formulation of jamming fitness is presented. Final y, a model of the CJWTA problem is constructed. In order to solve the CJWTA problem efficiently, a self-adaptive learning based discrete differential evolution （SLDDE） algorithm is proposed by introduc-ing a self-adaptive learning mechanism into the traditional discrete differential evolution algorithm. The SLDDE algorithm steers four candidate solution generation strategies simultaneously in the framework of the self-adaptive learning mechanism. Computa-tional simulations are conducted on ten test instances of CJWTA problem. The experimental results demonstrate that the proposed SLDDE algorithm not only can generate better results than only one strategy based discrete differential algorithms, but also outper-forms two algorithms which are proposed recently for the weapon-target assignment problems.展开更多
Path planning and formation structure forming are two of the most important problems for autonomous underwater vehicles(AUVs) to collaborate with each other.In this work,a dynamic formation model was proposed,in which...Path planning and formation structure forming are two of the most important problems for autonomous underwater vehicles(AUVs) to collaborate with each other.In this work,a dynamic formation model was proposed,in which several algorithms were developed for the complex underwater environment.Dimension changeable particle swarm algorithm was used to find an optimized path by dynamically adjusting the number and the distribution of the path nodes.Position relationship based obstacle avoidance algorithm was designed to detour along the edges of obstacles.Virtual potential point based formation-keeping algorithm was employed by incorporating dynamic strategies which were decided by the current states of the formation.The virtual potential point was used to keep the formation structure when the AUV or the formation was deviated.Simulation results show that an optimal path can be dynamically planned with fewer path nodes and smaller fitness,even with a concave obstacle.It has been also proven that different formation-keeping strategies can be adaptively selected and the formation can change its structure in a narrow area and restore back after passing the obstacle.展开更多
The existing trajectory clustering （TRACLUS） is sensitive to the input parameters c and MinLns. The parameter value is changed a little, but cluster results are entirely different. Aiming at this vulnerability, a sh...The existing trajectory clustering （TRACLUS） is sensitive to the input parameters c and MinLns. The parameter value is changed a little, but cluster results are entirely different. Aiming at this vulnerability, a shielding parameters sensitivity trajectory cluster （SPSTC） algorithm is proposed which is insensitive to the input parameters. Firstly, some definitions about the core distance and reachable distance of line segment are presented, and then the algorithm generates cluster sorting according to the core dis- tance and reachable distance. Secondly, the reachable plots of line segment sets are constructed according to the cluster sorting and reachable distance. Thirdly, a parameterized sequence is extracted according to the reachable plot, and then the final trajectory cluster based on the parameterized sequence is acquired. The parameterized sequence represents the inner cluster structure of trajectory data. Experiments on real data sets and test data sets show that the SPSTC algorithm effectively reduces the sensitivity to the input parameters, meanwhile it can obtain the better quality of the trajectory cluster.展开更多
Attribute reduction in the rough set theory is an important feature selection method, but finding a minimum attribute reduction has been proven to be a non-deterministic polynomial （NP）-hard problem. Therefore, it i...Attribute reduction in the rough set theory is an important feature selection method, but finding a minimum attribute reduction has been proven to be a non-deterministic polynomial （NP）-hard problem. Therefore, it is necessary to investigate some fast and effective approximate algorithms. A novel and enhanced quantum-inspired shuffled frog leaping based minimum attribute reduction algorithm （QSFLAR） is proposed. Evolutionary frogs are represented by multi-state quantum bits, and both quantum rotation gate and quantum mutation operators are used to exploit the mechanisms of frog population diversity and convergence to the global optimum. The decomposed attribute subsets are co-evolved by the elitist frogs with a quantum-inspired shuffled frog leaping algorithm. The experimental results validate the better feasibility and effectiveness of QSFLAR, comparing with some representa- tive algorithms. Therefore, QSFLAR can be considered as a more competitive algorithm on the efficiency and accuracy for minimum attribute reduction.展开更多
因为它的 insensitivity， 3D 脸识别吸引越来越多的注意到照明和姿势的变化。有在这个话题要解决的许多关键问题，例如 3D 脸表示和有效多特征熔化。在这份报纸，一个新奇 3D 脸识别算法被建议，它的性能在 BJUT-3D 脸数据库上被表明...因为它的 insensitivity， 3D 脸识别吸引越来越多的注意到照明和姿势的变化。有在这个话题要解决的许多关键问题，例如 3D 脸表示和有效多特征熔化。在这份报纸，一个新奇 3D 脸识别算法被建议，它的性能在 BJUT-3D 脸数据库上被表明。这个算法选择脸表面性质和相对关系矩阵的原则部件为脸表示特征。为每个特征的类似公制被定义。特征熔化策略被建议。它基于菲希尔是线性加权的策略线性判别式分析。最后，介绍算法在 BJUT-3D 脸数据库上被测试。算法和熔化策略的表演是令人满意的，这被结束。展开更多
Cooperative communication can achieve spatial diversity gains,and consequently combats signal fading due to multipath propagation in wireless networks powerfully.A novel complex field network-coded cooperation（CFNCC...Cooperative communication can achieve spatial diversity gains,and consequently combats signal fading due to multipath propagation in wireless networks powerfully.A novel complex field network-coded cooperation（CFNCC） scheme based on multi-user detection for the multiple unicast transmission is proposed.Theoretic analysis and simulation results demonstrate that,compared with the conventional cooperation（CC） scheme and network-coded cooperation（NCC） scheme,CFNCC would obtain higher network throughput and consumes less time slots.Moreover,a further investigation is made for the symbol error probability（SEP） performance of CFNCC scheme,and SEPs of CFNCC scheme are compared with those of NCC scheme in various scenarios for different signal to noise ratio（SNR） values.展开更多
With the development of the support vector machine（SVM）,the kernel function has become one of the cores of the research on SVM.To a large extent,the kernel function determines the generalization ability of the class...With the development of the support vector machine（SVM）,the kernel function has become one of the cores of the research on SVM.To a large extent,the kernel function determines the generalization ability of the classifier,but there is still no general theory to guide the choice and structure of the kernel function.An ensemble kernel function model based on the game theory is proposed,which is used for the SVM classification algorithm.The model can effectively integrate the advantages of the local kernel and the global kernel to get a better classification result,and can provide a feasible way for structuring the kernel function.By making experiments on some standard datasets,it is verified that the new method can significantly improve the accuracy of classification.展开更多
A distributed local adaptive transmit power assignment (LA-TPA) strategy was proposed to construct a topology with better performance according to the environment and application scenario and prolong the network lifet...A distributed local adaptive transmit power assignment (LA-TPA) strategy was proposed to construct a topology with better performance according to the environment and application scenario and prolong the network lifetime.It takes the path loss exponent and the energy control coefficient into consideration with the aim to accentuate the minimum covering district of each node more accurately and precisely according to various network application scenarios.Besides,a self-healing scheme that enhances the robustness of the network was provided.It makes the topology tolerate more dead nodes than existing algorithms.Simulation was done under OMNeT++ platform and the results show that the LA-TPA strategy is more effective in constructing a well-performance network topology based on various application scenarios and can prolong the network lifetime significantly.展开更多
基金Project(51901248)supported by the National Natural Science Foundation of ChinaProject(2023JJ40742)supported by the Natural Science Foundation of Hunan Province,China。
文摘In the present study,molecular dynamic simulation(MD)was used to investigate the plastic deformation process of the Fe-Mn alloys with different Mn contents.The influences of Mn contents ranging from 10%to 30%(at%)on the deformation behavior and the controlling mechanism of the Fe-base alloys were analyzed.The results show that phase transformations and{112}<111>_(BCC)deformation twinning occur in all Fe-Mn alloys but follow different deformation paths.In the Fe-10%Mn alloy the deformation twinning mechanism obeys the FCC-related path,the Fe-20%Mn alloy involves both the FCC-and HCP-related paths,and the deformation of the Fe-30%Mn alloy is dominated by the HCP-related twinning path.The addition of Mn can increase the stacking fault energy and retard the activation of slip systems as well as the formation of stacking faults.Thus,a higher content of Mn can delay the FCC®ε-martensite and the subsequentε-martensite®BCC phase transition at the intersection of twoε-martensitic bands.Therefore,the addition of Mn alloying element increases the yield strength and reduces the elastic modulus of the Fe-Mn alloys.The formation of deformation twins will contribute to the work-hardening effect and delay the necking and fracture of alloys.It is expected that the results in the present study will provide theoretical reference for the design and optimization of high-performance steels.
基金supported by the Major State Basic Research Program of China(B1420080204)National Science Fund for Distinguished Young Scholars(60725415)the National Natural Science Foundation of China(60606006)
文摘An effective algorithm based on signal coverage of effective communication and local energy-consumption saving strategy is proposed for the application in wireless sensor networks.This algorithm consists of two sub-algorithms.One is the multi-hop partition subspaces clustering algorithm for ensuring local energybalanced consumption ascribed to the deployment from another algorithm of distributed locating deployment based on efficient communication coverage probability（DLD-ECCP）.DLD-ECCP makes use of the characteristics of Markov chain and probabilistic optimization to obtain the optimum topology and number of sensor nodes.Through simulation,the relative data demonstrate the advantages of the proposed approaches on saving hardware resources and energy consumption of networks.
基金Projects(51104059,51204067)supported by the National Natural Science Foundation of ChinaProject(2012CB723103)supported the National Basic Research Program of China+3 种基金Project(IRT1235)supported by Innovation Team Development Plan of the Ministry of Education of ChinaProject(2013M531674)supported by China Postdoctoral Science FoundationProject(132300413203)supported by Basic and Frontier Technology Research Program of Henan Province,ChinaProject(WS2012B07)supported by the Open Project of State Key Laboratory Cultivation Base for Gas Geology and Gas Control(Henan Polytechnic University),China
文摘Focused on the Klinkenberg effect on gas seepage, the independently developed triaxial experimental system of gas seepage was applied to conduct research on the seepage characteristics of coal seam gas. By means of experimental data analysis and theoretical derivation, a calculation method of coal seam gas permeability was proposed, which synthesized the respective influences of gas dynamic viscosity, compressibility factor and Klinkenberg effect. The study results show that the Klinkenberg effect has a significant influence on the coal seam gas seepage, the permeability estimated with the method considering the Klinkenberg effect is correct, and this permeability can fully reflect the true seepage state of the gas. For the gas around the standard conditions, the influences of dynamic viscosity and compressibility factor on the permeability may be ignored. For the gas deviating far away from the standard conditions, the influences of dynamic viscosity and compressibility factor on the permeability must be considered. The research results have certain guiding significance in forming a correct understanding of the Klinkenberg effect and selecting a more accurate calculation method for the permeability of coal containing gas.
基金Supported by National Natural Science Foundation of China （60496322）, Natural Science Foundation of Beijing （4083034）, and Scientific Research Common Program of Beijing Municipal Commission.of Education （KM200610005020）_ _ _
基金Project(61701060)supported by the National Natural Science Foundation of China。
文摘Visual background extraction algorithm(ViBe)uses the first frame image to initialize the background model,which can easily introduce the“ghost”.Because ViBe uses the fixed segmentation threshold to achieve the foreground and background segmentation,the detection results in many false detections for the highly dynamic background.To solve these problems,an improved ghost suppression and adaptive Visual Background Extraction algorithm is proposed in this paper.Firstly,with the pixel’s temporal and spatial information,the historical pixels of a certain combination are used to initialize the background model in the odd frames of the video sequence.Secondly,the background sample set combined with the neighborhood pixels are used to determine a complex degree of the background,to acquire the adaptive segmentation threshold.Thirdly,the update rate is adjusted based on the complexity of the background.Finally,the detected result goes through a post-processing to achieve better detection results.The experimental results show that the improved algorithm will not only quickly suppress the“ghost”,but also have a better detection in a complex dynamic background.
基金supported by the National Natural Science Foundation of China(6113900261501229+1 种基金11547040)the Guangdong Natural Science Foundation(2016A030310051)
基金supported by the Natural Science Foundation of Jiangsu Province(BK2012237)
文摘The trustworthiness analysis and evaluation are the bases of the trust chain transfer. In this paper the formal method of trustworthiness analysis of a system based on the noninterfer- ence （NI） theory of the information flow is studied. Firstly, existing methods cannot analyze the impact of the system states on the trustworthiness of software during the process of trust chain trans- fer. To solve this problem, the impact of the system state on trust- worthiness of software is investigated, the run-time mutual interfer- ence behavior of software entitles is described and an interference model of the access control automaton of a system is established. Secondly, based on the intransitive noninterference （INI） theory, a formal analytic method of trustworthiness for trust chain transfer is proposed, providing a theoretical basis for the analysis of dynamic trustworthiness of software during the trust chain transfer process. Thirdly, a prototype system with dynamic trustworthiness on a plat- form with dual core architecture is constructed and a verification algorithm of the system trustworthiness is provided. Finally, the monitor hypothesis is extended to the dynamic monitor hypothe- sis, a theorem of static judgment rule of system trustworthiness is provided, which is useful to prove dynamic trustworthiness of a system at the beginning of system construction. Compared with previous work in this field, this research proposes not only a formal analytic method for the determination of system trustworthiness, but also a modeling method and an analysis algorithm that are feasible for practical implementation.
基金supported by the National Natural Science Foundation of China(6113900261171132+4 种基金61300167)the Natural Science Foundation of Jiangsu Education Department(12KJB520013)the Open Project Program of Jiangsu Provincial Key Laboratory of Computer Information Processing Technologythe Qing Lan Project of Jiangsu Provincethe Starting Foundation for Doctoral Scientific Research,Nantong University(14B20)
文摘To accelerate the selection process of feature subsets in the rough set theory （RST）, an ensemble elitist roles based quantum game （EERQG） algorithm is proposed for feature selec- tion. Firstly, the multilevel elitist roles based dynamics equilibrium strategy is established, and both immigration and emigration of elitists are able to be self-adaptive to balance between exploration and exploitation for feature selection. Secondly, the utility matrix of trust margins is introduced to the model of multilevel elitist roles to enhance various elitist roles＇ performance of searching the optimal feature subsets, and the win-win utility solutions for feature selec- tion can be attained. Meanwhile, a novel ensemble quantum game strategy is designed as an intriguing exhibiting structure to perfect the dynamics equilibrium of multilevel elitist roles. Finally, the en- semble manner of multilevel elitist roles is employed to achieve the global minimal feature subset, which will greatly improve the fea- sibility and effectiveness. Experiment results show the proposed EERQG algorithm has superiority compared to the existing feature selection algorithms.
基金Supported by National Natural Science Foundation Of China （60873235, 60473099）, Science-Technology Development Key Project of Jilin Province of China （20080318）, and Program of New Century Excellent Talents in University of China （NCET-06-0300）
基金supported by the National Natural Science Foundation of China(62171218)。
文摘As a typical industrial Internet of things(IIOT)service,demand response(DR)is becoming a promising enabler for intelligent energy management in 6 G-enabled smart grid systems,to achieve quick response for supply-demand mismatches.How-ever,existing literatures try to adjust customers’load profiles optimally,instead of electricity overhead,energy consumption patterns of residential appliances,customer satisfaction levels,and energy consumption habits.In this paper,a novel DR method is investigated by mixing the aforementioned factors,where the residential customer cluster is proposed to enhance the performance.Clustering approaches are leveraged to study the electricity consumption habits of various customers by extracting their features and characteristics from historical data.Based on the extracted information,the residential appliances can be scheduled effectively and flexibly.Moreover,we propose and study an efficient optimization framework to obtain the optimal scheduling solution by using clustering and deep learning methods.Extensive simulation experiments are conducted with real-world traces.Numerical results show that the proposed DR method and optimization framework outperform other baseline schemes in terms of the system overhead and peak-to-average ratio(PAR).The impact of various factors on the system utility is further analyzed,which provides useful insights on improving the efficiency of the DR strategy.With the achievement of efficient and intelligent energy management,the proposed method also promotes the realization of China’s carbon peaking and carbon neutrality goals.
基金supported by the National Natural Science Foundation of China (60873069 61171132)+3 种基金the Jiangsu Government Scholarship for Overseas Studies (JS-2010-K005)the Funding of Jiangsu Innovation Program for Graduate Education (CXZZ11 0219)the Open Project Program of Jiangsu Provincial Key Laboratory of Computer Information Processing Technology (KJS1023)the Applying Study Foundation of Nantong (BK2011062)
文摘Particle swarm optimization （PSO） is a new heuristic algorithm which has been applied to many optimization problems successfully. Attribute reduction is a key studying point of the rough set theory, and it has been proven that computing minimal reduc- tion of decision tables is a non-derterministic polynomial （NP）-hard problem. A new cooperative extended attribute reduction algorithm named Co-PSAR based on improved PSO is proposed, in which the cooperative evolutionary strategy with suitable fitness func- tions is involved to learn a good hypothesis for accelerating the optimization of searching minimal attribute reduction. Experiments on Benchmark functions and University of California, Irvine （UCI） data sets, compared with other algorithms, verify the superiority of the Co-PSAR algorithm in terms of the convergence speed, efficiency and accuracy for the attribute reduction.
基金supported by the Fundamental Research Funds for the Central Universities(NZ2013306)the Funding of Jiangsu Innovation Program for Graduate Education(CXLX11 0203)
文摘Cooperative jamming weapon-target assignment （CJWTA） problem is a key issue in electronic countermeasures （ECM）. Some symbols which relevant to the CJWTA are defined firstly. Then, a formulation of jamming fitness is presented. Final y, a model of the CJWTA problem is constructed. In order to solve the CJWTA problem efficiently, a self-adaptive learning based discrete differential evolution （SLDDE） algorithm is proposed by introduc-ing a self-adaptive learning mechanism into the traditional discrete differential evolution algorithm. The SLDDE algorithm steers four candidate solution generation strategies simultaneously in the framework of the self-adaptive learning mechanism. Computa-tional simulations are conducted on ten test instances of CJWTA problem. The experimental results demonstrate that the proposed SLDDE algorithm not only can generate better results than only one strategy based discrete differential algorithms, but also outper-forms two algorithms which are proposed recently for the weapon-target assignment problems.
基金Project(NS2013091)supported by the Basis Research Fund of Nanjing University of Aeronautics and Astronautics,China
文摘Path planning and formation structure forming are two of the most important problems for autonomous underwater vehicles(AUVs) to collaborate with each other.In this work,a dynamic formation model was proposed,in which several algorithms were developed for the complex underwater environment.Dimension changeable particle swarm algorithm was used to find an optimized path by dynamically adjusting the number and the distribution of the path nodes.Position relationship based obstacle avoidance algorithm was designed to detour along the edges of obstacles.Virtual potential point based formation-keeping algorithm was employed by incorporating dynamic strategies which were decided by the current states of the formation.The virtual potential point was used to keep the formation structure when the AUV or the formation was deviated.Simulation results show that an optimal path can be dynamically planned with fewer path nodes and smaller fitness,even with a concave obstacle.It has been also proven that different formation-keeping strategies can be adaptively selected and the formation can change its structure in a narrow area and restore back after passing the obstacle.
基金supported by the National High Technology Research and Development Program of China(863 Program)(2007AA01Z404)the Funding of Jiangsu Provincial Innovation Program for Graduate Education(CXLX110206)
文摘The existing trajectory clustering （TRACLUS） is sensitive to the input parameters c and MinLns. The parameter value is changed a little, but cluster results are entirely different. Aiming at this vulnerability, a shielding parameters sensitivity trajectory cluster （SPSTC） algorithm is proposed which is insensitive to the input parameters. Firstly, some definitions about the core distance and reachable distance of line segment are presented, and then the algorithm generates cluster sorting according to the core dis- tance and reachable distance. Secondly, the reachable plots of line segment sets are constructed according to the cluster sorting and reachable distance. Thirdly, a parameterized sequence is extracted according to the reachable plot, and then the final trajectory cluster based on the parameterized sequence is acquired. The parameterized sequence represents the inner cluster structure of trajectory data. Experiments on real data sets and test data sets show that the SPSTC algorithm effectively reduces the sensitivity to the input parameters, meanwhile it can obtain the better quality of the trajectory cluster.
基金supported by the National Natural Science Foundation of China(6113900261171132)+4 种基金the Funding of Jiangsu Innovation Program for Graduate Education(CXZZ11 0219)the Natural Science Foundation of Jiangsu Education Department(12KJB520013)the Applying Study Foundation of Nantong(BK2011062)the Open Project Program of State Key Laboratory for Novel Software Technology,Nanjing University(KFKT2012B28)the Natural Science Pre-Research Foundation of Nantong University(12ZY016)
文摘Attribute reduction in the rough set theory is an important feature selection method, but finding a minimum attribute reduction has been proven to be a non-deterministic polynomial （NP）-hard problem. Therefore, it is necessary to investigate some fast and effective approximate algorithms. A novel and enhanced quantum-inspired shuffled frog leaping based minimum attribute reduction algorithm （QSFLAR） is proposed. Evolutionary frogs are represented by multi-state quantum bits, and both quantum rotation gate and quantum mutation operators are used to exploit the mechanisms of frog population diversity and convergence to the global optimum. The decomposed attribute subsets are co-evolved by the elitist frogs with a quantum-inspired shuffled frog leaping algorithm. The experimental results validate the better feasibility and effectiveness of QSFLAR, comparing with some representa- tive algorithms. Therefore, QSFLAR can be considered as a more competitive algorithm on the efficiency and accuracy for minimum attribute reduction.
基金Supported by National Natural Science Foundation of China （60533030） and Beijing Natural Science Foundation （4061001）
文摘因为它的 insensitivity， 3D 脸识别吸引越来越多的注意到照明和姿势的变化。有在这个话题要解决的许多关键问题，例如 3D 脸表示和有效多特征熔化。在这份报纸，一个新奇 3D 脸识别算法被建议，它的性能在 BJUT-3D 脸数据库上被表明。这个算法选择脸表面性质和相对关系矩阵的原则部件为脸表示特征。为每个特征的类似公制被定义。特征熔化策略被建议。它基于菲希尔是线性加权的策略线性判别式分析。最后，介绍算法在 BJUT-3D 脸数据库上被测试。算法和熔化策略的表演是令人满意的，这被结束。
基金supported by the National Natural Science Foundation of China(6104000561001126+5 种基金61271262)the China Postdoctoral Science Foundation Funded Project(201104916382012T50789)the Natural Science Foundation of Shannxi Province of China(2011JQ8036)the Special Fund for Basic Scientific Research of Central Colleges (CHD2012ZD005)the Research Fund of Zhejiang University of Technology(20100244)
文摘Cooperative communication can achieve spatial diversity gains,and consequently combats signal fading due to multipath propagation in wireless networks powerfully.A novel complex field network-coded cooperation（CFNCC） scheme based on multi-user detection for the multiple unicast transmission is proposed.Theoretic analysis and simulation results demonstrate that,compared with the conventional cooperation（CC） scheme and network-coded cooperation（NCC） scheme,CFNCC would obtain higher network throughput and consumes less time slots.Moreover,a further investigation is made for the symbol error probability（SEP） performance of CFNCC scheme,and SEPs of CFNCC scheme are compared with those of NCC scheme in various scenarios for different signal to noise ratio（SNR） values.
基金supported by the National Natural Science Foundation of China(U1433116)the Aviation Science Foundation of China(20145752033)the Graduate Innovation Project of Jiangsu Province(KYLX15_0324)
文摘With the development of the support vector machine（SVM）,the kernel function has become one of the cores of the research on SVM.To a large extent,the kernel function determines the generalization ability of the classifier,but there is still no general theory to guide the choice and structure of the kernel function.An ensemble kernel function model based on the game theory is proposed,which is used for the SVM classification algorithm.The model can effectively integrate the advantages of the local kernel and the global kernel to get a better classification result,and can provide a feasible way for structuring the kernel function.By making experiments on some standard datasets,it is verified that the new method can significantly improve the accuracy of classification.
基金Projects(61101104,61100213) supported by the National Natural Science Foundation of ChinaProject(NY211050) supported by Fund of Nanjing University of Posts and Telecommunications,China
文摘A distributed local adaptive transmit power assignment (LA-TPA) strategy was proposed to construct a topology with better performance according to the environment and application scenario and prolong the network lifetime.It takes the path loss exponent and the energy control coefficient into consideration with the aim to accentuate the minimum covering district of each node more accurately and precisely according to various network application scenarios.Besides,a self-healing scheme that enhances the robustness of the network was provided.It makes the topology tolerate more dead nodes than existing algorithms.Simulation was done under OMNeT++ platform and the results show that the LA-TPA strategy is more effective in constructing a well-performance network topology based on various application scenarios and can prolong the network lifetime significantly.
