Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 9 of 9
Full-Text Articles in Physical Sciences and Mathematics
Research On Social Network Inference Method Based On Observation Data, Hailiang Chen, Bin Chen, Yuan Peng, Dong Jian, Chuan Ai
Research On Social Network Inference Method Based On Observation Data, Hailiang Chen, Bin Chen, Yuan Peng, Dong Jian, Chuan Ai
Journal of System Simulation
Abstract: Internet technology and online social networks have developed rapidly, which enables people to randomly express their opinions, ideas, emotional exchanges and economic exchanges. Inferring social networks is made possible through the observation data exchanged by people on the Internet. Through the analysis of ConNIe (Convex Network Inference) algorithm, this paper researches the effects of sparse parameter, propagation time distribution model and its parameters on the inference results of the algorithm. According to the analysis, a social network inference framework based on ConNIe algorithm is proposed. Combining the perceptron and particle swarm optimization algorithm, the ConNIe algorithm inference becomes a …
Jammer Placement Algorithm Based On Particle Swarm Optimization, Fang Fang, Chunming Ye, Haibo Liu
Jammer Placement Algorithm Based On Particle Swarm Optimization, Fang Fang, Chunming Ye, Haibo Liu
Journal of System Simulation
Abstract: A novel jammer placement algorithm based on particle swarm optimization is proposed to solve the problems of nodes’ mobility and restrictions on placement areas in ad-hoc network. There are three steps in this algorithm: network simulation, jamming simulation, and optimization. The algorithm simulates the network communication process and movement of nodes with discrete simulation method. Simple particle swarm optimization is applied to compute the exact coordinates of jammers. Experiment results show that this algorithm is good at jamming network nodes moving in different ways. The algorithm has stable performance with varying conditions such as different placement areas, jamming …
Multi-Seats Collaborative Task Planning Based On Improved Particle Swarm Optimization, Cai Rui, Wang Wei, Jue Qu, Hu Bo
Multi-Seats Collaborative Task Planning Based On Improved Particle Swarm Optimization, Cai Rui, Wang Wei, Jue Qu, Hu Bo
Journal of System Simulation
Abstract: Aiming at the allocation conflict between task and operator of multi-seats collaborative task planning in command and control cabin, a multi-seats collaborative task planning method based on improved particle swarm optimization is proposed. This method describes and analyzes the multi-seats collaborative task and establishes a solution space model based on task sequence. In solving the model, the particle swarm optimization (PSO) was improved by using multi-dimensional asynchronous processing and modifying inertia weight parameters so that the efficiency and local searching ability of the PSO were improved. The example analysis shows that the model and the algorithm can effectively reduce …
Multi-Strategy Cooperative Evolutionary Pso Based On Cauchy Mutation Strategy, Yongji Wang, Tingting Su, Liu Lei
Multi-Strategy Cooperative Evolutionary Pso Based On Cauchy Mutation Strategy, Yongji Wang, Tingting Su, Liu Lei
Journal of System Simulation
Abstract: For improving the performance of particle swarm optimization (PSO) in optimization simulation, a multi-strategy cooperative evolutionary PSO based on Cauchy mutation strategy is proposed. The new algorithm divides the whole swarm into three sub-swarms. A part of particles is selected to Cauchy mutation with a certain probability, and the rest of particles adjust their exploitation and exploration by different evolutionary strategies (large-scale search strategy, local search strategy, and adaptive velocity updating strategy). The sub-swarms share their information to achieve cooperation. Three strategies are used to optimize three test functions, and the result shows the advantages …
Prediction Of Aircraft Cabin Energy Consumption Based On Pso And Cro Algorithms, Xiuyan Wang, Yanmin Liu, Gewen Zhang, Zongshuai Li, Jiaquan Lin
Prediction Of Aircraft Cabin Energy Consumption Based On Pso And Cro Algorithms, Xiuyan Wang, Yanmin Liu, Gewen Zhang, Zongshuai Li, Jiaquan Lin
Journal of System Simulation
Abstract: To meet the requirements of the rapidity and the accuracy of the aircraft cabin energy consumption prediction for bridge-load air conditioner when an aircraft berthing, a forecasting method based on the combination of neural network, particle swarm and coral reef is proposed. The energy consumption prediction model is established based on wavelet neural network, and the prediction model parameters are optimized using the united algorithm of coral reefs and particle swarm optimization. The united algorithm adopts a double-layer structure: the data of the first layer are grouped and optimized by the particle swarm optimization algorithm for a preliminary optimization, …
Error Estimation For Material Simulation Data Based On Hybrid Learning Algorithm, Wang Juan, Xiaoyu Yang, Zongguo Wang, Ren Jie, Xushan Zhao
Error Estimation For Material Simulation Data Based On Hybrid Learning Algorithm, Wang Juan, Xiaoyu Yang, Zongguo Wang, Ren Jie, Xushan Zhao
Journal of System Simulation
Abstract: In order to obtain high quality material simulation data from Density Functional Theory material calculation software package, a modeling method based on BP neural network was proposed to build model estimating the error of material simulation data. A novel hybrid algorithm combining simple particle swarm optimization algorithm that excludes speed item with BP algorithm, also referred to tsPSO-BP, was proposed to optimize the connection weights of the BP neural network. The hybrid learning algorithm not only makes use of strong global searching ability of the PSO, but also strong local searching ability of the BP algorithm. The BP …
Target Decision In Collaborative Air Combats Using Multi-Agent Particle Swarm Optimization, Yuewen Fu, Yuancheng Wang, Chen Zhen, Wenlan Fan
Target Decision In Collaborative Air Combats Using Multi-Agent Particle Swarm Optimization, Yuewen Fu, Yuancheng Wang, Chen Zhen, Wenlan Fan
Journal of System Simulation
Abstract: Under the research background of collaborative multi-aircraft and multi-target air combats, combined with the actual combat constraint conditions and the threat assessment functions on both sides, a collaborative air combat target decision simulation model is established for complex and changeable battlefield situations, which can reflect the priority of fire attack. To solve the decision scheme quickly and accurately, an improved multi-agent particle swarm optimization algorithm is proposed by introducing the interaction mechanism of the multi-agent theory into particle swarm optimization algorithm; and the neighborhood cooperation operator, mutation operator and self-learning operator for the agent are designed respectively. …
Prediction Of Alumina Density Based On Lssvm, Guimei Cui, Haijin Yang, Piliang Liu, Yu Kai
Prediction Of Alumina Density Based On Lssvm, Guimei Cui, Haijin Yang, Piliang Liu, Yu Kai
Journal of System Simulation
Abstract: The prediction model of alumina density based on the PSO algorithm with swarm activity to optimize LSSVM method is built. According to the production process characteristics of aluminum electrolysis and historical data, the input variables of the model is determined. It can solve these problems that Particle Swarm Optimization (PSO) algorithm is with the risk of premature convergence and least square support vector machine is time consuming with parameter selection. The method uses swarm activity as diversity index. When swarm activity is quickened to descend, evolution operation is added to modify the positions or velocities of particles to …
Optimization Design Of Fuzzy Energy Management For Plug-In Hybrid Electric Vehicles, Xiaolan Wu, Zhifeng Bai, Xiaohui Shi, Binggang Cao
Optimization Design Of Fuzzy Energy Management For Plug-In Hybrid Electric Vehicles, Xiaolan Wu, Zhifeng Bai, Xiaohui Shi, Binggang Cao
Journal of System Simulation
Abstract: Because of complex system configuration, it is difficult to find precise mathematics model of PHEV drivetrain. The fuzzy controller design depends mainly on expert’s experience and has much subjectivity. A fuzzy energy management strategy (EMS) based on particle swarm optimization (PSO) is presented. In this EMS, the fuzzy rules obtained from expert knowledge are unaltered and the PSO is used to optimize the parameters of membership functions of the fuzzy controller. The provided EMS model is built by Matlab/simulink and embedded in the Advisor software for simulation and comparative analysis. The result shows that, compared with the conventional …