Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Keyword
-
- Simulation (135)
- Path planning (76)
- Genetic algorithm (48)
- Deep learning (44)
- Numerical simulation (44)
-
- Digital twin (42)
- Virtual reality (42)
- Modeling and simulation (39)
- Multi-objective optimization (39)
- Particle swarm optimization (35)
- Reinforcement learning (34)
- Modeling (33)
- Fault diagnosis (29)
- Attention mechanism (28)
- Deep reinforcement learning (28)
- Neural network (26)
- UAV (26)
- Simulation model (25)
- Complex network (22)
- System simulation (22)
- System dynamics (21)
- Visualization (21)
- Virtual simulation (20)
- DRL (19)
- Optimization (19)
- Multi-agent (18)
- Trajectory planning (18)
- Traffic simulation (17)
- Unity3D (17)
- A* algorithm (16)
- Publication Year
- Publication
-
- Journal of System Simulation (3880)
- All Dissertations (1)
- Computational Modeling & Simulation Engineering Theses & Dissertations (1)
- Department of Agricultural and Biological Systems Engineering: Presentations and White Papers (1)
- Doctoral Dissertations and Master's Theses (1)
-
- Electrical & Computer Engineering Faculty Publications (1)
- Electronic Theses, Projects, and Dissertations (1)
- Engineering Management & Systems Engineering Theses & Dissertations (1)
- Journal of Nonprofit Innovation (1)
- Military Cyber Affairs (1)
- Open Access Theses & Dissertations (1)
- Publications (1)
- Publications and Research (1)
- SMU Data Science Review (1)
- Social Science - All Scholarship (1)
- Theses, Dissertations and Capstones (1)
- Publication Type
Articles 571 - 600 of 3895
Full-Text Articles in Systems Science
Research On Path Planning Of Warehouse Robot With Improved Harris Hawks Algorithm, Xu Lei, Jingyi Chen, Xiaoyang Chen
Research On Path Planning Of Warehouse Robot With Improved Harris Hawks Algorithm, Xu Lei, Jingyi Chen, Xiaoyang Chen
Journal of System Simulation
Abstract: To improve the path planning efficiency of warehouse mobile robots in static environments, and to solve the problems of slow convergence and local optimum of traditional Harris Hawk (HHO) algorithm in path planning, a Harris Hawk optimization algorithm based on Tent chaotic mapping fused with Cauchy's back-learning variant (TCLHHO) is proposed. The population diversity is increased by Tent Chaotic mapping to speed up convergence. An exponential prey escape energy updating strategy is proposed to balance the global search and local exploitation capabilities of the algorithm. The optimal individual is disturbed by Cauchy mutation operator and inverse learning strategy to …
Image Self-Enhancement De-Hazing Algorithm Combined With Generative Adversarial Network, Wanjun Liu, Yuqian Cheng, Haicheng Qu
Image Self-Enhancement De-Hazing Algorithm Combined With Generative Adversarial Network, Wanjun Liu, Yuqian Cheng, Haicheng Qu
Journal of System Simulation
Abstract: To solve the problem that existing dehazing models are prone to over fitting after training with synthetic hazy image data sets, an image self-enhancement dehazing algorithm is proposed in combination with generative adversarial network. The depth information of an image is estimated while combining two Generative Adversarial Networks. The first GAN uses a clear image to learn the process of image hazing, and then adopts the hazed image generated by it as the input of the second GAN to guide the second GAN to correct dehazing. In order to reduce the difference before and after image processing, the consistency …
Cooperative And Optimal Control Of Multiple Mimo Objects Under Information Sharing, Jiong Shao, Xinchun Jie, Meng Wu
Cooperative And Optimal Control Of Multiple Mimo Objects Under Information Sharing, Jiong Shao, Xinchun Jie, Meng Wu
Journal of System Simulation
Abstract: Aiming at the problems of low cooperative efficiency and slow convergence of control algorithm for multiple MIMO objects in cyber-physical system (CPS), a cooperative optimization control strategy for multiple MIMO objects under the condition of information sharing is proposed. A new network control system structure with only physical layer and information layer is used to realize real-time sharing of state variables, control and detection information of multiple MIMO objects. Under the condition of information sharing, based on the performance indexes assigned by CPS and the physical constraints between each object, the cooperative controller designed by minimum principle realizes the …
Research On Collaborative Optimization Method Of Multi-Uav Task Allocation And Path Planning, Peng Xiao, Feng Xie, Haihong Ni, Min Zhang, Zhili Tang, Ni Li
Research On Collaborative Optimization Method Of Multi-Uav Task Allocation And Path Planning, Peng Xiao, Feng Xie, Haihong Ni, Min Zhang, Zhili Tang, Ni Li
Journal of System Simulation
Abstract: Aiming at the task requirements of multi-UAV to perform multi-target collaborative reconnaissance, a collaborative optimization method of multi-machine and multi-objective task allocation and path planning is proposed. Based on the partheno genetic algorithms (PGA), a cost function combined with the actual path cost is constructed through the Dubins curve. To further reduce the calculation cost, a clustering algorithm based on UAV detection distance is proposed, and the generated clustering point is used as a new waypoint of UAV. The simulation results show that considering the dangerous area and the large number of reconnaissance points, the algorithm can effectively complete …
Tri-Training Algorithm Based On Density Peaks Clustering, Yuhang Luo, Runxiu Wu, Zhihua Cui, Yiying Zhang, Yeshen He, Jia Zhao
Tri-Training Algorithm Based On Density Peaks Clustering, Yuhang Luo, Runxiu Wu, Zhihua Cui, Yiying Zhang, Yeshen He, Jia Zhao
Journal of System Simulation
Abstract: Tri-training can effectively improve the generalization ability of classifiers by using unlabeled data for classification, but it is prone to mislabeling unlabeled data, thus forming training noise. Tritraining (Tri-training with density peaks clustering, DPC-TT) algorithm based on density peaks clustering is proposed. The DPC-TT algorithm uses the density peaks clustering algorithm to obtain the class cluster centers and local densities of the training data, and the samples within the truncation distance of the class cluster centers are identified as the samples with better spatial structure, and these samples are labeled as the core data, and the classifier is updated …
Deep Learning Based Local Path Planning Method For Moving Robots, Zesen Liu, Sheng Bi, Chuanhong Guo, Yankui Wang, Min Dong
Deep Learning Based Local Path Planning Method For Moving Robots, Zesen Liu, Sheng Bi, Chuanhong Guo, Yankui Wang, Min Dong
Journal of System Simulation
Abstract: In order to integrate visual information into the robot navigation process, improve the robot's recognition rate of various types of obstacles, and reduce the occurrence of dangerous events, a local path planning network based on two-dimensional CNN and LSTM is designed, and a local path planning approach based on deep learning is proposed. The network uses the image from camera and the global path to generate the current steering angle required for obstacle avoidance and navigation. A simulated indoor scene is built for training and validating the network. A path evaluation method that uses the total length and the …
Path Planning Of Unmanned Delivery Vehicle Based On Improved Q-Learning Algorithm, Xiaokang Wang, Jie Ji, Yang Liu, Qing He
Path Planning Of Unmanned Delivery Vehicle Based On Improved Q-Learning Algorithm, Xiaokang Wang, Jie Ji, Yang Liu, Qing He
Journal of System Simulation
Abstract: To solve the traditional Q-learning algorithm for unmanned vehicle path planning suffers from the problems of low planning efficiency and slow convergence speed, for this reason, a path planning algorithm for unmanned delivery vehicles based on the improved Q-learning algorithm is proposed. Learning from the energy iteration principle of the simulated annealing algorithm, adjusts the greedy factor ε to make it change dynamically during the training process, so as to balance the relationship between exploration and utilization, and thus improve the planning efficiency. The reward value in the reward mechanism is changed from a discrete value to a continuous …
Research On Simulation Methods For Forest Fire Extinguishing Using Water Mist, Bing Xiang, Xiaohong Dong, Yang Li
Research On Simulation Methods For Forest Fire Extinguishing Using Water Mist, Bing Xiang, Xiaohong Dong, Yang Li
Journal of System Simulation
Abstract: As a highly hazardous natural disaster, the occurrence and spread of forest fires are usually affected by a variety of complex factors such as climate, terrain, vegetation, combustible materials, etc., which makes it difficult to accurately simulate the spread and extinguishing process of forest fires. The spread of forest fires and the process of water mist fire extinguishing are physically modele. The spread model adopts a tree module structure to simulate the pyrolysis reaction of tree burning, and considers the effects of temperature, wind field,mass loss rate and other factors on the spread of tree burning.In the fire extinguishing …
Time Slot Allocation Method Of Data Link Based On Improved Difference Algorithm, Yuting Zhu, Huankun Su, Xiaodong Feng, Shijie Lei, Yanfang Fu
Time Slot Allocation Method Of Data Link Based On Improved Difference Algorithm, Yuting Zhu, Huankun Su, Xiaodong Feng, Shijie Lei, Yanfang Fu
Journal of System Simulation
Abstract: Aiming at the problems of single algorithm, being prone to local optima, and weak generalization ability of the current strategies, based on an improved differential evolutionary algorithm, a chaos algorithm, an adaptive variational crossover algorithm, and a problem solution processing mechanism, a time slot allocation strategy is proposed. The chaos algorithm is used to initialize the population to increase the diversity and avoid the premature convergence. The selection probability parameter is then used to make the crossover and variation process more flexible, expanding the search range in early to increase the possibility of global optima in late. The experiment …
Research On Verification Method Of Missile Elastic Suppression Based On Frequency Compensation, Rixin Su, Ou Zhang
Research On Verification Method Of Missile Elastic Suppression Based On Frequency Compensation, Rixin Su, Ou Zhang
Journal of System Simulation
Abstract: For the elastic model of missile body in six degree of freedom mathematical simulation, the research on the verification method of elastic vibration suppression is carried out.. The notch filter used for elastic vibration suppression is introduced, the verification idea for filter design in boost-phase and passive-phase stages of missile flight is analyzed, and the problem currently existing in mathematical simulation verification is pointed out. Based on the frequency modulation phenomenon, an online verification method of frequency compensation for the notch filter is put forward, and it can be found that the function can be applied to any order …
Gradient-Based Deep Reinforcement Learning Interpretation Methods, Yuan Wang, Lin Xu, Xiaoze Gong, Yongliang Zhang, Yongli Wang
Gradient-Based Deep Reinforcement Learning Interpretation Methods, Yuan Wang, Lin Xu, Xiaoze Gong, Yongliang Zhang, Yongli Wang
Journal of System Simulation
Abstract: The learning process and working mechanism of deep reinforcement learning methods such as DQN are not transparent, and their decision basis and reliability cannot be perceived, which makes the decisions made by the model highly questionable and greatly limits the application scenarios of deep reinforcement learning. To explain the decision-making mechanism of intelligent agents, this paper proposes a gradient based saliency map generation algorithm SMGG. It uses the gradient information of feature maps generated by high-level convolutional layers to calculate the importance of different feature maps. With the known structure and internal parameters of the model, starting from the …
Prediction Of Converter Gas Generation Based On Intermission Production Improved Elman, Jiajie Fei, Dinghui Wu, Junyan Fan, Jing Wang
Prediction Of Converter Gas Generation Based On Intermission Production Improved Elman, Jiajie Fei, Dinghui Wu, Junyan Fan, Jing Wang
Journal of System Simulation
Abstract: Aiming at large fluctuations of intermission and low prediction accuracy in iron and steel industry, based on the classification of intermission characteristics, a converter gas generation predicting model(CPSO-Elman) based on Elman neural network(ENN) optimized by chaotic PSO(CPSO) algorithm is proposed. The intermittent characteristics of converter gas generation time series are extracted and raw data is classified according to intermittent duration. The PSO algorithm improved by chaotic disturbance is introduced to optimize the initial weight and threshold of ENN and inertia weight of nonlinear updating is designed to balance global search ability and local search ability. Construct the combined prediction …
Generative Machine Learning For Cyber Security, James Halvorsen, Dr. Assefaw Gebremedhin
Generative Machine Learning For Cyber Security, James Halvorsen, Dr. Assefaw Gebremedhin
Military Cyber Affairs
Automated approaches to cyber security based on machine learning will be necessary to combat the next generation of cyber-attacks. Current machine learning tools, however, are difficult to develop and deploy due to issues such as data availability and high false positive rates. Generative models can help solve data-related issues by creating high quality synthetic data for training and testing. Furthermore, some generative architectures are multipurpose, and when used for tasks such as intrusion detection, can outperform existing classifier models. This paper demonstrates how the future of cyber security stands to benefit from continued research on generative models.
Intelligent Optimization Method Of Cloud Manufacturing Swarm Based On Incomplete Information Game, Kunpeng Zhang, Yan Wang, Zhicheng Ji
Intelligent Optimization Method Of Cloud Manufacturing Swarm Based On Incomplete Information Game, Kunpeng Zhang, Yan Wang, Zhicheng Ji
Journal of System Simulation
Abstract: In the process of cloud manufacturing, the incomplete information status and the mutual competition and restriction relationship between cloud platform operator and demander lead to the difficult choice of manufacturing services. A cloud manufacturing swarm intelligent optimization method based on incomplete information game model is proposed. A static game model based on incomplete information is established for the interest competition between demand-side and cloud platform, with the goal of rationally pursuing the maximization of their own revenue function. The competition rules between demand-side and cloud platform are proposed, which are introduced into nature through Harsanyi transformation and converted into …
Hyper-Heuristic Approach With K-Means Clustering For Inter-Cell Scheduling, Yanlin Zhao, Yunna Tian
Hyper-Heuristic Approach With K-Means Clustering For Inter-Cell Scheduling, Yanlin Zhao, Yunna Tian
Journal of System Simulation
Abstract: According to the actual production situation of China's manufacturing industry, a hyperheuristic algorithm based on K-means clustering is proposed for inter-cell scheduling problem of flexible job-shop. K-means clustering is applied to group entities with similar attributes into the corresponding work cluster decision blocks, and the ant colony algorithm is used to select heuristic rules for each decision block. The optimal scheduling solutions are generated by using corresponding heuristic rules for scheduling of entities in each decision block. Computational results show that, the computational granularity is properly increased by the form of decision blocks, and the computational efficiency of the …
Asl-Catboost Method For Wind Turbine Fault Detection Integrated With Digital Twin, Hongtao Liang, Lingchao Kong, Guozhu Liu, Wenxuan Dong, Xiangyi Liu
Asl-Catboost Method For Wind Turbine Fault Detection Integrated With Digital Twin, Hongtao Liang, Lingchao Kong, Guozhu Liu, Wenxuan Dong, Xiangyi Liu
Journal of System Simulation
Abstract: In view of the low visibility of the current wind farm status monitoring and insufficient realtime operation and maintenance, based on the concept of digital twin five-dimensional model, the framework of wind farm digital twin five-dimensional model is constructed. Aiming at the insufficient fault detection capability of traditional algorithms and unbalanced positive and negative samples in fan fault data set, the improved ASL-CatBoost algorithm is proposed to achieve the accurate detection of fan fault status. Based on the digital twinning platform, combined with MATLAB/Simulink, the simulation mathematical model of doubly-fed wind turbine under the condition of blade mass imbalance …
Distributed Energy Management Strategy Of Microgrid Based On Master-Slave Game, Miaomiao Ma, Hao Wang, Lipeng Dong, Xiangjie Liu
Distributed Energy Management Strategy Of Microgrid Based On Master-Slave Game, Miaomiao Ma, Hao Wang, Lipeng Dong, Xiangjie Liu
Journal of System Simulation
Abstract: Under the operation mode of power market, based on two-layer master-slave game, a distributed energy management strategy for the microgrid is proposed to tackle the conflict between the overall optimal operation of renewable microgrid and the maximum profit of each investor. To fully consider the balance between energy supply and demand, the concept of power trading agent is introduced, and an integrated demand response strategy based on consumer satisfaction and adjustable load is proposed on the user side. Considering the initiative and decision-making ability of power supply and load, the decision-making game model is established with power trading agent …
Optimization Of Urban Traffic Microsimulation Model For Carbon Emission Reduction, Bo Liu, Jianxin Lin, Yini Liu, Dong Zhang
Optimization Of Urban Traffic Microsimulation Model For Carbon Emission Reduction, Bo Liu, Jianxin Lin, Yini Liu, Dong Zhang
Journal of System Simulation
Abstract: To assess the environmental benefits of transportation management or control strategies, a method to effectively integrate the micro-traffic simulation model and the micro-vehicle emission model is proposed. VISSIM platform is used to build a case micro traffic simulation model. K-means clustering method is used to divide the driving behavior into 4 types based on the acceleration and deceleration characteristics of different speed intervals of the trajectory data, and the global parameters of the simulation model are calibrated based on the driving characteristics, which quantitatively describe the total sensitivity of the parameters and the sensitivity of the interactions between the …
Modeling And Analysis Of Hybrid Traffic Flow Considering Actual Behavior Of Platoon, Xi Wang, Xiujian Yang, Xiaohan Jia, Shenyi Wang
Modeling And Analysis Of Hybrid Traffic Flow Considering Actual Behavior Of Platoon, Xi Wang, Xiujian Yang, Xiaohan Jia, Shenyi Wang
Journal of System Simulation
Abstract: To explore the effect of actual behavior of autonomous vehicular platoon on traffic flow, aiming at the hybrid traffic flow mixed with predecessor following(PF) platoon which is modeled according to the actual control strategy, a hybrid traffic flow model is established based on cellular automata(CA) modeling method. Simulation analysis shows that the effect of platoon characteristics such as time headway, market penetration, platoon size, and control gains on hybrid traffic flow presents coupling and nonlinear properties. The spatiotemporal behavior of hybrid traffic flow with different platoon characteristics is generally much different. Reducing time headway or increasing platoon market penetration …
Dynamic Path Planning For Mobile Robot Based On Rrt* And Dynamic Window Approach, Rui Zhang, Li Zhou, Zhengyang Liu
Dynamic Path Planning For Mobile Robot Based On Rrt* And Dynamic Window Approach, Rui Zhang, Li Zhou, Zhengyang Liu
Journal of System Simulation
Abstract: A dynamic path planning method combining RRT* and dynamic window approach(DWA) is proposed to realize the obstacle avoidance of mobile robot in complex environment of dynamic obstacles. Improved RRT* algorithm is used to generate the global optimal safe path based on the known environment information. By eliminating the dangerous nodes generated by RRT* algorithm, the security of global path is ensured. Greedy algorithm is used to remove the redundant nodes in the path to reduce the length of global path. DWA is used to track along the global optimal path planned by the improved RRT* algorithm. When static obstacles …
Collaborative Navigation Method For 5g Cluster Uav Based On Configuration Optimization, Chao Gao, Zheng Huang, Xuan Zhao, Hongxing Wang, Tao Long
Collaborative Navigation Method For 5g Cluster Uav Based On Configuration Optimization, Chao Gao, Zheng Huang, Xuan Zhao, Hongxing Wang, Tao Long
Journal of System Simulation
Abstract: The existing range based cooperative navigation methods for clustered UAVs generally ignore the impact of space configuration on positioning and energy determination, which makes it difficult to obtain the accurate navigation and positioning results. In view of this, a collaborative navigation method is proposed for 5G clustered UAVs based on spatial configuration optimization. The relative ranging error model of UAVs based on 5G signals in complex environments is constructed, and the optimization strategy for collaborative navigation nodes is established based on the minimum geometric division of precision(GDOP) criterion to achieve the real-time optimization of collaborative navigation spatial configuration; A …
A Multi-Uav Collaborative Priority Coverage Search Algorithm, Xiang Yu, Qianrui Deng, Sirui Duan, Chen Jiang
A Multi-Uav Collaborative Priority Coverage Search Algorithm, Xiang Yu, Qianrui Deng, Sirui Duan, Chen Jiang
Journal of System Simulation
Abstract: For the challenges such as large disaster area, uneven distribution of key areas and limited rescue time in emergency rescue, a multi-UAV collaborative priority coverage search algorithm is proposed. The search area is rasterized, and each grid is probabilistically labeled according to the disaster prediction information. The search area is divided into sub-regions of similar size and equal number of UAVs by K-means++ algorithm, and the search starting point of each sub-region is determined based on the clustering center, so that the multiple UAVs can carry out the partition cooperative search of the whole area. The score of each …
Incremental Image Dehazing Algorithm Based On Multiple Transfer Attention, Jinyang Wei, Keping Wang, Yi Yang, Shumin Fei
Incremental Image Dehazing Algorithm Based On Multiple Transfer Attention, Jinyang Wei, Keping Wang, Yi Yang, Shumin Fei
Journal of System Simulation
Abstract: In order to improve the processing ability of the depth-neural network dehazing algorithm to the supplementary data set, and to make the network differently process the image features of different importance to improve the dehazing ability of the network, an incremental dehazing algorithm based on multiple migration of attention is proposed. The teacher's attention generation network in the form of Encoder-Decoder extracts the multiple attention of labels and haze, which is used it as the label of the characteristic migration media network to constrain the network training to form the migration media attention as close as possible to the …
Path Planning Rapid Algorithm Based On Modified Rrt* For Unmanned Surface Vessel, Zhaozhen Jiang, Wenlong Wang, Wenqi Sun
Path Planning Rapid Algorithm Based On Modified Rrt* For Unmanned Surface Vessel, Zhaozhen Jiang, Wenlong Wang, Wenqi Sun
Journal of System Simulation
Abstract: Aiming at the weak purposiveness of rapidly exploring random tree algorithm in USV path planning, a modified rapid algorithm is proposed. The artificial potential field method is improved and the force analysis in four directions is added to comprehensively calculate the resultant force on USV. The calculation method of steering angle is redefined to avoid entering the local optimal trap and can reach the target point smoothly to obtain an initial path. The initial path is used to set the random point sampling area of rapidly exploring random tree algorithm. By reducing the probability of random points generated in …
Research On Cross-Domain Unmanned Swarm Cooperative Anti-Submarine Search Method, Ning Wang, Xiaolong Liang, Jiaqiang Zhang, Yueqi Hou, Aiwu Yang
Research On Cross-Domain Unmanned Swarm Cooperative Anti-Submarine Search Method, Ning Wang, Xiaolong Liang, Jiaqiang Zhang, Yueqi Hou, Aiwu Yang
Journal of System Simulation
Abstract: For the maritime ASW search, a cross-domain unmanned swarm cooperative search method is proposed in which USVs are used as the communication relay of UAVs. The digital grid map is used to characterize the mission area and the kinematic model of cross-domain platform is constructed. The cooperative method of cross-domain unmanned systems is proposed, and the distributed information fusion mechanism of unmanned systems is designed. The search objective function for heterogeneous platforms is designed to guide the unmanned systems to make real-time decisions in search task. The simulation results show that the proposed method can be effective to the …
Simulation Verification And Decision-Making Key Technologies Of Unmanned Swarm Game Confrontation: A Survey, Xiaolong Liang, Aiwu Yang, Jiaqiang Zhang, Yueqi Hou, Ning Wang, Xiao Huang, Junbin Gong
Simulation Verification And Decision-Making Key Technologies Of Unmanned Swarm Game Confrontation: A Survey, Xiaolong Liang, Aiwu Yang, Jiaqiang Zhang, Yueqi Hou, Ning Wang, Xiao Huang, Junbin Gong
Journal of System Simulation
Abstract: Unmanned swarm game confrontation is a new combat mode and plays a crucial role in intelligent warfare. Its core is the autonomous generation of a series of game confrontation decision sequences to "empower" the swarm. The progress of system simulation verification for the unmanned swarm game confrontation is analyzed. The key technologies of the autonomous decision-making are discussed from three aspects, technology based on expert systems and game theory, technology based on swarm intelligence and optimization theory, and technology based on neural networks and reinforcement learning. The key technology research conducted by the author's team on the autonomous decisionmaking …
Research On Integration Of Virtual-Real Hybrid Simulation Experiment Environment For Unmanned Swarm, Huijie Yang, Taoshun Xiao, Chen Wu, Lingfeng Guo
Research On Integration Of Virtual-Real Hybrid Simulation Experiment Environment For Unmanned Swarm, Huijie Yang, Taoshun Xiao, Chen Wu, Lingfeng Guo
Journal of System Simulation
Abstract: Constructing the experiment environment and researching the core technology, key equipment and operation theory is the key step for the development of unmanned swarm. Based on the requirement of hybrid simulation environment for unmanned swarm, the elements of the experiment environment are analyzed, and the architecture is proposed, which is composed of common infrastructure, general experiment services, special experiment tools, security and support tool. The key experiment environment integration technology is studied from the aspects of experiment network, model data and experiment application. The feasibility of the method to construct the virtual-real hybrid simulation environment is verified by an …
Mixed-Variable Particle Swarm Optimization Algorithm Based On Competitive Coevolution, Hu Zhang, Heng Zhang, Zilu Huang, Zhe Wang, Qingpo Fu, Jin Peng, Feng Wang
Mixed-Variable Particle Swarm Optimization Algorithm Based On Competitive Coevolution, Hu Zhang, Heng Zhang, Zilu Huang, Zhe Wang, Qingpo Fu, Jin Peng, Feng Wang
Journal of System Simulation
Abstract: For the current algorithm, it is difficult to obtain the available solution due to the irregularity of problem decision space caused by the numerous mixed variable optimization problems during real industrial applications. The coevolution strategy is introduced and a mixed variable particle swarm optimization algorithm(CCPSO) based on competitive coevolution is proposed. The search direction adjustment mechanism based on tolerance is designed to judge the evolution state of particles, adaptively adjust the search direction of particles, avoid falling into local optimum, and balance the convergence and diversity of the population. The learning object generation mechanism is adopted for each particle …
Handling Constrained Multi-Objective Optimization Problems Based On Relationship Between Pareto Fronts, Yubo Wang, Chengyu Hu, Wenyin Gong
Handling Constrained Multi-Objective Optimization Problems Based On Relationship Between Pareto Fronts, Yubo Wang, Chengyu Hu, Wenyin Gong
Journal of System Simulation
Abstract: To address the challenges of balancing the constraint satisfaction and objective function optimization, and dealing with the complex feasible regions in constrained multi-objective optimization problems(CMOPs), a classification-based search approach is proposed based on different Pareto front relationships. A dual-population dual-phase framework is proposed in which an auxiliary population Pa and a main population Pm are evolved and the evolution process is divided into a learning phase and a search phase. During the learning phase, Pa explores unconstrained Pareto front (UPF) and Pm explores constrained Pareto front(CPF), through which the relationship between UPF and CPF is determined. After completing the …
Element Grouping Faceted Fully Connected Network Based On Ris, Shunhu Hou, Shengliang Fang, Qingyao Zeng, Mengtao Wang
Element Grouping Faceted Fully Connected Network Based On Ris, Shunhu Hou, Shengliang Fang, Qingyao Zeng, Mengtao Wang
Journal of System Simulation
Abstract: In view of the over-fitting problem that caused by multiple parameters and high memory usage of the full connection layer of neural network in training, a RIS-based element grouping areal fully connected neural network (RGFCNN) is proposed for the first time based on the structural characteristics of reconfigurable intelligence surface (RIS). Based on the structural characteristics of RIS, the network is optimized on traditional FCNN. A novel transmission surface attention mechanism is designed for the effective feature extraction of data. Compared with the traditional FCNNs, the proposed network does not arrange the data in one-dimensional manner. Instead, a element …