Robust and efficient AUV path planning is a key element for persistence AUV maneuvering in variable underwater environments. To develop such a path planning system, in this study, differential evolution(DE) algorithm ...Robust and efficient AUV path planning is a key element for persistence AUV maneuvering in variable underwater environments. To develop such a path planning system, in this study, differential evolution(DE) algorithm is employed. The performance of the DE-based planner in generating time-efficient paths to direct the AUV from its initial conditions to the target of interest is investigated within a complexed 3D underwater environment incorporated with turbulent current vector fields, coastal area,islands, and static/dynamic obstacles. The results of simulations indicate the inherent efficiency of the DE-based path planner as it is capable of extracting feasible areas of a real map to determine the allowed spaces for the vehicle deployment while coping undesired current disturbances, exploiting desirable currents, and avoiding collision boundaries in directing the vehicle to its destination. The results are implementable for a realistic scenario and on-board real AUV as the DE planner satisfies all vehicular and environmental constraints while minimizing the travel time/distance, in a computationally efficient manner.展开更多
A self-adaptive differential evolution neutron spectrum unfolding algorithm(SDENUA)is established in this study to unfold the neutron spectra obtained from a water-pumping-injection multilayered concentric sphere neut...A self-adaptive differential evolution neutron spectrum unfolding algorithm(SDENUA)is established in this study to unfold the neutron spectra obtained from a water-pumping-injection multilayered concentric sphere neutron spectrometer(WMNS).Specifically,the neutron fluence bounds are estimated to accelerate the algorithm convergence,and the minimum error between the optimal solution and input neutron counts with relative uncertainties is limited to 10^(-6)to avoid unnecessary calculations.Furthermore,the crossover probability and scaling factor are self-adaptively controlled.FLUKA Monte Carlo is used to simulate the readings of the WMNS under(1)a spectrum of Cf-252 and(2)its spectrum after being moderated,(3)a spectrum used for boron neutron capture therapy,and(4)a reactor spectrum.Subsequently,the measured neutron counts are unfolded using the SDENUA.The uncertainties of the measured neutron count and the response matrix are considered in the SDENUA,which does not require complex parameter tuning or an a priori default spectrum.The results indicate that the solutions of the SDENUA agree better with the IAEA spectra than those of MAXED and GRAVEL in UMG 3.1,and the errors of the final results calculated using the SDENUA are less than 12%.The established SDENUA can be used to unfold spectra from the WMNS.展开更多
A novel multi-objective optimization algorithm incorporating vector method and evolution strategies,referred as vector dominant multi-objective evolutionary algorithm(VD-MOEA),is developed and applied to the aerodynam...A novel multi-objective optimization algorithm incorporating vector method and evolution strategies,referred as vector dominant multi-objective evolutionary algorithm(VD-MOEA),is developed and applied to the aerodynamic-structural integrative design of wind turbine blades.A set of virtual vectors are elaborately constructed,guiding population to fast move forward to the Pareto optimal front and dominating the distribution uniformity with high efficiency.In comparison to conventional evolution algorithms,VD-MOEA displays dramatic improvement of algorithm performance in both convergence and diversity preservation when handling complex problems of multi-variables,multi-objectives and multi-constraints.As an example,a 1.5 MW wind turbine blade is subsequently designed taking the maximum annual energy production,the minimum blade mass,and the minimum blade root thrust as the optimization objectives.The results show that the Pareto optimal set can be obtained in one single simulation run and that the obtained solutions in the optimal set are distributed quite uniformly,maximally maintaining the population diversity.The efficiency of VD-MOEA has been elevated by two orders of magnitude compared with the classical NSGA-II.This provides a reliable high-performance optimization approach for the aerodynamic-structural integrative design of wind turbine blade.展开更多
Although the phase-shift seismic processing method has characteristics of high accuracy, good stability, high efficiency, and high-dip imaging, it is not able to adapt to strong lateral velocity variation. To overcome...Although the phase-shift seismic processing method has characteristics of high accuracy, good stability, high efficiency, and high-dip imaging, it is not able to adapt to strong lateral velocity variation. To overcome this defect, a finite-difference method in the frequency-space domain is introduced in the migration process, because it can adapt to strong lateral velocity variation and the coefficient is optimized by a hybrid genetic and simulated annealing algorithm. The two measures improve the precision of the approximation dispersion equation. Thus, the imaging effect is improved for areas of high-dip structure and strong lateral velocity variation. The migration imaging of a 2-D SEG/EAGE salt dome model proves that a better imaging effect in these areas is achieved by optimized phase-shift migration operator plus a finite-difference method based on a hybrid genetic and simulated annealing algorithm. The method proposed in this paper is better than conventional methods in imaging of areas of high-dip angle and strong lateral velocity variation.展开更多
the existing information diffusion models focus on analyzing the spatial distribution of certain pieces of messages in social networks. However, these conventional models ignored another important characteristic of di...the existing information diffusion models focus on analyzing the spatial distribution of certain pieces of messages in social networks. However, these conventional models ignored another important characteristic of diffusion: gradually changing of message contents due to the ‘new' and ‘comment' mechanisms. A novel genetic-algorithm-based information evolution model is proposed to reproduce both the diffusion and development process of information in social networks. This model firstly proposes a five-tuple to represent three types of topics: independent, competitive and mutually exclusive. Furthermore, it adopts mutation operator and forms new crossover and mutation rules to simulate four typical interactions between individuals, which bring the advantage of reproducing the information evolution process in both popularity and content.A series of experiments tested on public datasets demonstrate that: 1) independent and competitive topics of information rarely affect each other while mutually exclusive topics significantly suppress the diffusion processes of each other; 2) lower mutation probability leads to decreasing of final information amount. The experimental results show that our evolution model is more reasonable and feasible in demonstrating the evolution of information in social networks.展开更多
Using similar single-difference methodology(SSDM) to solve the deformation values of the monitoring points, there is unstability of the deformation information series, at sometimes.In order to overcome this shortcomin...Using similar single-difference methodology(SSDM) to solve the deformation values of the monitoring points, there is unstability of the deformation information series, at sometimes.In order to overcome this shortcoming, Kalman filtering algorithm for this series is established,and its correctness and validity are verified with the test data obtained on the movable platform in plane. The results show that Kalman filtering can improve the correctness, reliability and stability of the deformation information series.展开更多
A new algorithm is proposed for underwater vehicles multi-path planning. This algorithm is based on fitness sharing genetic algorithm, clustering and evolution of multiple populations, which can keep the diversity of ...A new algorithm is proposed for underwater vehicles multi-path planning. This algorithm is based on fitness sharing genetic algorithm, clustering and evolution of multiple populations, which can keep the diversity of the solution path, and decrease the operating time because of the independent evolution of each subpopulation. The multi-path planning algorithm is demonstrated by a number of two-dimensional path planning problems. The results show that the multi-path planning algorithm has the following characteristics: high searching capability, rapid convergence and high reliability.展开更多
There has been a growing interest in mathematical models to character the evolutionary algorithms. The best-known one of such models is the axiomatic model called the abstract evolutionary algorithm （AEA）, which uni...There has been a growing interest in mathematical models to character the evolutionary algorithms. The best-known one of such models is the axiomatic model called the abstract evolutionary algorithm （AEA）, which unifies most of the currently known evolutionary algorithms and describes the evolution as an abstract stochastic process composed of two fundamental abstract operators： abstract selection and evolution operators. In this paper, we first introduce the definitions of the generalized abstract selection and evolution operators. Then we discuss the characterization of some parameters related to generalized abstract selection and evolution operators. Based on these operators, we finally give the strong convergence of the generalized abstract evolutionary algorithm. The present work provides a big step toward the establishment of a unified theory of evolutionary computation.展开更多
In this paper, we propose a mathe- matical model for long reach Passive Optical Networks （PON） planning. The model consid- ers the traffic demand, user requirements and physical constraints. It can support conven- t...In this paper, we propose a mathe- matical model for long reach Passive Optical Networks （PON） planning. The model consid- ers the traffic demand, user requirements and physical constraints. It can support conven- tional star-like topologies as well as cascade PON networks. Then a two-stage evolutional algorithm is described to solve this problem. The first stage was to find a proper splitter can- didate site set, composing the outer loop. The second stage aimed to get the optimal topology when the splitter locations were selected, com- posing the internal loop. In this algorithm, the Pr/ifer sequence is used to build up a one-to-one correspondence between a PON network configuration and a chromosome. Compared with the results obtained by the enumeration method, the proposed model and algorithm are shown to be effective and accu- rate.展开更多
For the purpose of developing an immune function on production accidents in a petrochemical enterprise, a new cultivation-evolution approach of preventive mechanism is suggested by analyzing various factors relating t...For the purpose of developing an immune function on production accidents in a petrochemical enterprise, a new cultivation-evolution approach of preventive mechanism is suggested by analyzing various factors relating to immune deficiency syndrome and by referring to immunity genetic algorithm and relevant concepts applied in medicine science. Accident-immunity system for highly hazardous petrochemical enterprise, which is made up of its productive system＇s Safety Organ and Safety Organization, is typically an evolution-cultivation progress for immune function, The new B immune cell is generated after several layers＇ screening, clone expanding, receptor editing, organizing in immune system of work accident in petrochemical enterprise. There is a B immune cell with high appetency and a manipulative function chain for accident-immunity. Taking the antigen of accidents in industry as the target function and the immune antibody as the solution, the authors carried out a computation diagram for prediction of appetency between the antigen and antibody.展开更多
A modified alternating direction implicit algorithm is proposed to solve the full-vectorial finite-difference beam propagation method formulation based on H fields. The cross-coupling terms are neglected in the first ...A modified alternating direction implicit algorithm is proposed to solve the full-vectorial finite-difference beam propagation method formulation based on H fields. The cross-coupling terms are neglected in the first sub-step, but evaluated and doubly used in the second sub-step. The order of two sub-steps is reversed for each transverse magnetic field component so that the cross-coupling terms are always expressed in implicit form, thus the calculation is very efficient and stable. Moreover, an improved six-point finite-difference scheme with high accuracy independent of specific structures of waveguide is also constructed to approximate the cross-coupling terms along the transverse directions. The imaginary-distance procedure is used to assess the validity and utility of the present method. The field patterns and the normalized propagation constants of the fundamental mode for a buried rectangular waveguide and a rib waveguide are presented. Solutions are in excellent agreement with the benchmark results from the modal transverse resonance method.展开更多
The thinking of co evolution is applied to the optimization of retaining and protecting structure for deep foundation excavation, and the system of optimization of anchored row piles for deep foundation pit has been a...The thinking of co evolution is applied to the optimization of retaining and protecting structure for deep foundation excavation, and the system of optimization of anchored row piles for deep foundation pit has been already developed successfully. For the co evolution algorithm providing an evolutionary mechanism to simulate ever changing problem space, it is an optimization algorithm that has high performance, especially applying to the optimization of complicated system of retaining and protecting for deep foundation pit. It is shown by many engineering practices that the co evolution algorithm has obvious optimization effect, so it can be an important method of optimization of retaining and protecting for deep foundation pit. Here the authors discuss the co evolution model, object function, all kinds of constraint conditions and their disposal methods, and several key techniques of system realization.展开更多
Efficient electrocatalysts are crucial for hydrogen generation from electrolyzing water.Nevertheless,the conventional"trial and error"method for producing advanced electrocatalysts is not only cost-ineffecti...Efficient electrocatalysts are crucial for hydrogen generation from electrolyzing water.Nevertheless,the conventional"trial and error"method for producing advanced electrocatalysts is not only cost-ineffective but also time-consuming and labor-intensive.Fortunately,the advancement of machine learning brings new opportunities for electrocatalysts discovery and design.By analyzing experimental and theoretical data,machine learning can effectively predict their hydrogen evolution reaction(HER)performance.This review summarizes recent developments in machine learning for low-dimensional electrocatalysts,including zero-dimension nanoparticles and nanoclusters,one-dimensional nanotubes and nanowires,two-dimensional nanosheets,as well as other electrocatalysts.In particular,the effects of descriptors and algorithms on screening low-dimensional electrocatalysts and investigating their HER performance are highlighted.Finally,the future directions and perspectives for machine learning in electrocatalysis are discussed,emphasizing the potential for machine learning to accelerate electrocatalyst discovery,optimize their performance,and provide new insights into electrocatalytic mechanisms.Overall,this work offers an in-depth understanding of the current state of machine learning in electrocatalysis and its potential for future research.展开更多
On the basis of sorting out current understanding of solid bitumen (SB) in shales and taking organic-rich shales in the first member of the Cretaceous Qingshankou Formation in the Songliao Basin as an example, the def...On the basis of sorting out current understanding of solid bitumen (SB) in shales and taking organic-rich shales in the first member of the Cretaceous Qingshankou Formation in the Songliao Basin as an example, the definition, classification, occurrence and evolution path of SB are systemtically studied, and the indicative significance of SB reflectance (Rob) on maturity and its influence on the development of reservoir space are discussed and summarized. The results show that the difference of primary maceral types is primarily responsible for the different evolution paths of SB. Most of the pre-oil bitumen is in-situ SB with only a small amount being of migrated SB, while most of the post-oil bitumen and pyrobitumen are migrated SB. From the immature to early oil maturity stage, bituminite, vitrinite, and inertinite can be distinguished from SB based on their optical characteristics under reflected light, and alginite can be differentiated from SB by their fluorescence characteristics. Under scanning electron microscope, in-situ SB and migrated SB can be effectively identified. Rob increases linearly with increasing vitrinite reflectance (Ro), as a result of a decrease of aliphatic structure and the enhancement of aromatization of SB. Within the oil window three types of secondary pores may develop in SB, including modified mineral pores, devolatilization cracks and bubble holes. At a high maturity stage spongy pores may develop in pyrobitumen. Scanning electron microscopy combined with in-situ SEM-Raman spectroscopy can further reveal the structral information of different types of SB, thus providing crucial data for understanding for understanding OM migration paths, dynamics, and distances at micro-scale.展开更多
The purpose of this paper is to expand Trivedi’s study on the influence of channel structure ,which based on product difference, to cost difference; and analyze the evolution course of channel structure under differe...The purpose of this paper is to expand Trivedi’s study on the influence of channel structure ,which based on product difference, to cost difference; and analyze the evolution course of channel structure under different conditions. We find that like product difference, cost difference have important influence on the choice of channel structure. This paper has improved the present result and provided proof for the choice of channel structure under different environments.展开更多
为设计高效稳定的演化算法,将方程求根的不动点迭代思想引入到优化领域,通过将演化算法的寻优过程看作为在迭代框架下方程不动点的逐步显示化过程,设计出一种基于数学模型的演化新算法,即不动点演化算法(fixed point evolution algorith...为设计高效稳定的演化算法,将方程求根的不动点迭代思想引入到优化领域,通过将演化算法的寻优过程看作为在迭代框架下方程不动点的逐步显示化过程,设计出一种基于数学模型的演化新算法,即不动点演化算法(fixed point evolution algorithm,FPEA).该算法的繁殖算子是由Aitken加速的不动点迭代模型导出的二次多项式,其整体框架继承传统演化算法(如差分演化算法)基于种群的迭代模式.试验结果表明:在基准函数集CEC2014、CEC2019上,本文算法的最优值平均排名在所有比较算法中排名第1;在4个工程约束设计问题上,FPEA与CSA、GPE等多个算法相比,能以较少的计算开销获得最高的求解精度.展开更多
文摘Robust and efficient AUV path planning is a key element for persistence AUV maneuvering in variable underwater environments. To develop such a path planning system, in this study, differential evolution(DE) algorithm is employed. The performance of the DE-based planner in generating time-efficient paths to direct the AUV from its initial conditions to the target of interest is investigated within a complexed 3D underwater environment incorporated with turbulent current vector fields, coastal area,islands, and static/dynamic obstacles. The results of simulations indicate the inherent efficiency of the DE-based path planner as it is capable of extracting feasible areas of a real map to determine the allowed spaces for the vehicle deployment while coping undesired current disturbances, exploiting desirable currents, and avoiding collision boundaries in directing the vehicle to its destination. The results are implementable for a realistic scenario and on-board real AUV as the DE planner satisfies all vehicular and environmental constraints while minimizing the travel time/distance, in a computationally efficient manner.
基金supported by the National Key R&D Program of the MOST of China(No.2016YFA0300204)the National Natural Science Foundation of China(Nos.11227902)as part of the Si PáME2beamline project+1 种基金supported by the National Natural Science Foundation of China(No.41774120)the Sichuan Science and Technology Program(No.2021YJ0329)。
文摘A self-adaptive differential evolution neutron spectrum unfolding algorithm(SDENUA)is established in this study to unfold the neutron spectra obtained from a water-pumping-injection multilayered concentric sphere neutron spectrometer(WMNS).Specifically,the neutron fluence bounds are estimated to accelerate the algorithm convergence,and the minimum error between the optimal solution and input neutron counts with relative uncertainties is limited to 10^(-6)to avoid unnecessary calculations.Furthermore,the crossover probability and scaling factor are self-adaptively controlled.FLUKA Monte Carlo is used to simulate the readings of the WMNS under(1)a spectrum of Cf-252 and(2)its spectrum after being moderated,(3)a spectrum used for boron neutron capture therapy,and(4)a reactor spectrum.Subsequently,the measured neutron counts are unfolded using the SDENUA.The uncertainties of the measured neutron count and the response matrix are considered in the SDENUA,which does not require complex parameter tuning or an a priori default spectrum.The results indicate that the solutions of the SDENUA agree better with the IAEA spectra than those of MAXED and GRAVEL in UMG 3.1,and the errors of the final results calculated using the SDENUA are less than 12%.The established SDENUA can be used to unfold spectra from the WMNS.
基金funded jointly by the National Basic Research Program of China(″973″Program)(No2014CB046200)the National Natural Science Foundation of China(No.51506089)+1 种基金the Jiangsu Provincial Natural Science Foundation(No.BK20140059)the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘A novel multi-objective optimization algorithm incorporating vector method and evolution strategies,referred as vector dominant multi-objective evolutionary algorithm(VD-MOEA),is developed and applied to the aerodynamic-structural integrative design of wind turbine blades.A set of virtual vectors are elaborately constructed,guiding population to fast move forward to the Pareto optimal front and dominating the distribution uniformity with high efficiency.In comparison to conventional evolution algorithms,VD-MOEA displays dramatic improvement of algorithm performance in both convergence and diversity preservation when handling complex problems of multi-variables,multi-objectives and multi-constraints.As an example,a 1.5 MW wind turbine blade is subsequently designed taking the maximum annual energy production,the minimum blade mass,and the minimum blade root thrust as the optimization objectives.The results show that the Pareto optimal set can be obtained in one single simulation run and that the obtained solutions in the optimal set are distributed quite uniformly,maximally maintaining the population diversity.The efficiency of VD-MOEA has been elevated by two orders of magnitude compared with the classical NSGA-II.This provides a reliable high-performance optimization approach for the aerodynamic-structural integrative design of wind turbine blade.
基金the Open Fund(PLC201104)of State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (Chengdu University of Technology)the National Natural Science Foundation of China(No.61072073)the Key Project of Education Commission of Sichuan Province(No.10ZA072)
文摘Although the phase-shift seismic processing method has characteristics of high accuracy, good stability, high efficiency, and high-dip imaging, it is not able to adapt to strong lateral velocity variation. To overcome this defect, a finite-difference method in the frequency-space domain is introduced in the migration process, because it can adapt to strong lateral velocity variation and the coefficient is optimized by a hybrid genetic and simulated annealing algorithm. The two measures improve the precision of the approximation dispersion equation. Thus, the imaging effect is improved for areas of high-dip structure and strong lateral velocity variation. The migration imaging of a 2-D SEG/EAGE salt dome model proves that a better imaging effect in these areas is achieved by optimized phase-shift migration operator plus a finite-difference method based on a hybrid genetic and simulated annealing algorithm. The method proposed in this paper is better than conventional methods in imaging of areas of high-dip angle and strong lateral velocity variation.
基金supported by the National Key Basic Research Program of China (No. 2013CB329603)National Natural Science Foundation (No.61562004,No.61431008)Basic Research Foundation of Shanghai Committee of Science and Technology (No. 13JC1403501) of China
文摘the existing information diffusion models focus on analyzing the spatial distribution of certain pieces of messages in social networks. However, these conventional models ignored another important characteristic of diffusion: gradually changing of message contents due to the ‘new' and ‘comment' mechanisms. A novel genetic-algorithm-based information evolution model is proposed to reproduce both the diffusion and development process of information in social networks. This model firstly proposes a five-tuple to represent three types of topics: independent, competitive and mutually exclusive. Furthermore, it adopts mutation operator and forms new crossover and mutation rules to simulate four typical interactions between individuals, which bring the advantage of reproducing the information evolution process in both popularity and content.A series of experiments tested on public datasets demonstrate that: 1) independent and competitive topics of information rarely affect each other while mutually exclusive topics significantly suppress the diffusion processes of each other; 2) lower mutation probability leads to decreasing of final information amount. The experimental results show that our evolution model is more reasonable and feasible in demonstrating the evolution of information in social networks.
文摘Using similar single-difference methodology(SSDM) to solve the deformation values of the monitoring points, there is unstability of the deformation information series, at sometimes.In order to overcome this shortcoming, Kalman filtering algorithm for this series is established,and its correctness and validity are verified with the test data obtained on the movable platform in plane. The results show that Kalman filtering can improve the correctness, reliability and stability of the deformation information series.
文摘A new algorithm is proposed for underwater vehicles multi-path planning. This algorithm is based on fitness sharing genetic algorithm, clustering and evolution of multiple populations, which can keep the diversity of the solution path, and decrease the operating time because of the independent evolution of each subpopulation. The multi-path planning algorithm is demonstrated by a number of two-dimensional path planning problems. The results show that the multi-path planning algorithm has the following characteristics: high searching capability, rapid convergence and high reliability.
基金Supported by the National Science Foundation of China(60133010)Supported by the Science Foundation of Henan Province(2000110019)
文摘There has been a growing interest in mathematical models to character the evolutionary algorithms. The best-known one of such models is the axiomatic model called the abstract evolutionary algorithm （AEA）, which unifies most of the currently known evolutionary algorithms and describes the evolution as an abstract stochastic process composed of two fundamental abstract operators： abstract selection and evolution operators. In this paper, we first introduce the definitions of the generalized abstract selection and evolution operators. Then we discuss the characterization of some parameters related to generalized abstract selection and evolution operators. Based on these operators, we finally give the strong convergence of the generalized abstract evolutionary algorithm. The present work provides a big step toward the establishment of a unified theory of evolutionary computation.
基金supported by National High Technology Research and Development Program of China under Grant No.2011AA01A104National 973 Program underGrant No. 2013CB329204National Natural Science Foundation of China under Grant No.61100206
文摘In this paper, we propose a mathe- matical model for long reach Passive Optical Networks （PON） planning. The model consid- ers the traffic demand, user requirements and physical constraints. It can support conven- tional star-like topologies as well as cascade PON networks. Then a two-stage evolutional algorithm is described to solve this problem. The first stage was to find a proper splitter can- didate site set, composing the outer loop. The second stage aimed to get the optimal topology when the splitter locations were selected, com- posing the internal loop. In this algorithm, the Pr/ifer sequence is used to build up a one-to-one correspondence between a PON network configuration and a chromosome. Compared with the results obtained by the enumeration method, the proposed model and algorithm are shown to be effective and accu- rate.
文摘For the purpose of developing an immune function on production accidents in a petrochemical enterprise, a new cultivation-evolution approach of preventive mechanism is suggested by analyzing various factors relating to immune deficiency syndrome and by referring to immunity genetic algorithm and relevant concepts applied in medicine science. Accident-immunity system for highly hazardous petrochemical enterprise, which is made up of its productive system＇s Safety Organ and Safety Organization, is typically an evolution-cultivation progress for immune function, The new B immune cell is generated after several layers＇ screening, clone expanding, receptor editing, organizing in immune system of work accident in petrochemical enterprise. There is a B immune cell with high appetency and a manipulative function chain for accident-immunity. Taking the antigen of accidents in industry as the target function and the immune antibody as the solution, the authors carried out a computation diagram for prediction of appetency between the antigen and antibody.
文摘A modified alternating direction implicit algorithm is proposed to solve the full-vectorial finite-difference beam propagation method formulation based on H fields. The cross-coupling terms are neglected in the first sub-step, but evaluated and doubly used in the second sub-step. The order of two sub-steps is reversed for each transverse magnetic field component so that the cross-coupling terms are always expressed in implicit form, thus the calculation is very efficient and stable. Moreover, an improved six-point finite-difference scheme with high accuracy independent of specific structures of waveguide is also constructed to approximate the cross-coupling terms along the transverse directions. The imaginary-distance procedure is used to assess the validity and utility of the present method. The field patterns and the normalized propagation constants of the fundamental mode for a buried rectangular waveguide and a rib waveguide are presented. Solutions are in excellent agreement with the benchmark results from the modal transverse resonance method.
基金National Natural Science Foundation of China( 5 986 80 0 1)
文摘The thinking of co evolution is applied to the optimization of retaining and protecting structure for deep foundation excavation, and the system of optimization of anchored row piles for deep foundation pit has been already developed successfully. For the co evolution algorithm providing an evolutionary mechanism to simulate ever changing problem space, it is an optimization algorithm that has high performance, especially applying to the optimization of complicated system of retaining and protecting for deep foundation pit. It is shown by many engineering practices that the co evolution algorithm has obvious optimization effect, so it can be an important method of optimization of retaining and protecting for deep foundation pit. Here the authors discuss the co evolution model, object function, all kinds of constraint conditions and their disposal methods, and several key techniques of system realization.
基金This work was supported by the National Natural Science Foundation of China(Grant No.22008098,52122408)the Program for Science&Technology Innovation Talents in Universities of Henan Province(No.22HASTIT008)+3 种基金the Programs for Science and Technology Development of Henan Province,China(No.222102320065)the Key Specialized Research and Development Breakthrough(Science and Technology)in Henan Province(No.212102210214)the Natural Science Foundations of Henan Province(No.222300420502)the Key Scientific Research Projects of University in Henan Province(No.23B430002).
文摘Efficient electrocatalysts are crucial for hydrogen generation from electrolyzing water.Nevertheless,the conventional"trial and error"method for producing advanced electrocatalysts is not only cost-ineffective but also time-consuming and labor-intensive.Fortunately,the advancement of machine learning brings new opportunities for electrocatalysts discovery and design.By analyzing experimental and theoretical data,machine learning can effectively predict their hydrogen evolution reaction(HER)performance.This review summarizes recent developments in machine learning for low-dimensional electrocatalysts,including zero-dimension nanoparticles and nanoclusters,one-dimensional nanotubes and nanowires,two-dimensional nanosheets,as well as other electrocatalysts.In particular,the effects of descriptors and algorithms on screening low-dimensional electrocatalysts and investigating their HER performance are highlighted.Finally,the future directions and perspectives for machine learning in electrocatalysis are discussed,emphasizing the potential for machine learning to accelerate electrocatalyst discovery,optimize their performance,and provide new insights into electrocatalytic mechanisms.Overall,this work offers an in-depth understanding of the current state of machine learning in electrocatalysis and its potential for future research.
基金Supported by the the National Natural Science Foundation of China(U22A201550).
文摘On the basis of sorting out current understanding of solid bitumen (SB) in shales and taking organic-rich shales in the first member of the Cretaceous Qingshankou Formation in the Songliao Basin as an example, the definition, classification, occurrence and evolution path of SB are systemtically studied, and the indicative significance of SB reflectance (Rob) on maturity and its influence on the development of reservoir space are discussed and summarized. The results show that the difference of primary maceral types is primarily responsible for the different evolution paths of SB. Most of the pre-oil bitumen is in-situ SB with only a small amount being of migrated SB, while most of the post-oil bitumen and pyrobitumen are migrated SB. From the immature to early oil maturity stage, bituminite, vitrinite, and inertinite can be distinguished from SB based on their optical characteristics under reflected light, and alginite can be differentiated from SB by their fluorescence characteristics. Under scanning electron microscope, in-situ SB and migrated SB can be effectively identified. Rob increases linearly with increasing vitrinite reflectance (Ro), as a result of a decrease of aliphatic structure and the enhancement of aromatization of SB. Within the oil window three types of secondary pores may develop in SB, including modified mineral pores, devolatilization cracks and bubble holes. At a high maturity stage spongy pores may develop in pyrobitumen. Scanning electron microscopy combined with in-situ SEM-Raman spectroscopy can further reveal the structral information of different types of SB, thus providing crucial data for understanding for understanding OM migration paths, dynamics, and distances at micro-scale.
基金Supported by the National Preeminence Youth Foundation of China(No.79275002)
文摘The purpose of this paper is to expand Trivedi’s study on the influence of channel structure ,which based on product difference, to cost difference; and analyze the evolution course of channel structure under different conditions. We find that like product difference, cost difference have important influence on the choice of channel structure. This paper has improved the present result and provided proof for the choice of channel structure under different environments.
文摘由于高视距(Line of Sight,LOS)的空对地通信,无人机(Unmanned Aerial Vehicle,UAV)通信网络容易遭受窃听者的截获。为此,针对智能反射面(Intelligent Reflecting Surface,IRS)辅助UAV通信系统,提出基于改进差分进化算法的安全速率优化(Optimal Secrecy Rate Based on Improved Differential Evolution,OSR-IDE)算法,进而提升系统的安全速率。将IRS与UAV结合,提升信号传输质量。OSR-IDE算法联合优化UAV传输的波束赋形(Passive Beamforming,PBF)、IRS相移、IRS和UAV位置来最大化系统的安全速率。建立最大化系统安全速率优化问题模型,利用改进的差分进化算法求解。仿真结果表明,OSR-IDE算法的安全速率优于基准算法。
文摘为设计高效稳定的演化算法,将方程求根的不动点迭代思想引入到优化领域,通过将演化算法的寻优过程看作为在迭代框架下方程不动点的逐步显示化过程,设计出一种基于数学模型的演化新算法,即不动点演化算法(fixed point evolution algorithm,FPEA).该算法的繁殖算子是由Aitken加速的不动点迭代模型导出的二次多项式,其整体框架继承传统演化算法(如差分演化算法)基于种群的迭代模式.试验结果表明:在基准函数集CEC2014、CEC2019上,本文算法的最优值平均排名在所有比较算法中排名第1;在4个工程约束设计问题上,FPEA与CSA、GPE等多个算法相比,能以较少的计算开销获得最高的求解精度.
