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检索条件"主题词=particle swarm optimization algorithm"

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Study on Comprehensive optimization Method in the Performance of a New Type of High-speed USV and Its Analysis

Study on Comprehensive Optimization Method in the Performanc...

引用

2016 International Conference on Modeling, Simulation and optimization Technologies and Applications（MSOTA 2016）

作者： Zifan Wei Songlin Yang Shengping Jing Man Liu Jiangsu Modern Shipbuilding Technology Co Ltd Jiangsu University of Science and Technology

ISBN: (纸本)9781510835702

Taking the comprehensive performance of a new type of high-speed unmanned surface vehicle(USV) including its rapidity, maneuverability, seakeeping and overturning resistance into consideration, this paper establishes a mathematical model of the performance comprehensive optimization of high-speed USV. And according to the mathematical model and optimization algorithm, comprehensive optimization software based on a variety of optimization algorithms was designed and compiled to analyze the relevant calculation. The results indicates that the optimization effect of the growth mechanism is more superior to the roulette mechanism;genetic algorithm of growth mechanism and particle swarm optimization algorithm would have the best results in the optimization of the 5000 th generation, and it can get the rapidity optimization system had greater influence on the total optimization system;and what's more, the optimal values of hull length and other key design variables and partial parameters of different algorithms are obtained.

关键词： high-speed USV comprehensive optimization genetic algorithm particle swarm optimization algorithm key variables

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RESEARCH ON INTRUSION DETECTION OF SVM BASED ON PSO

RESEARCH ON INTRUSION DETECTION OF SVM BASED ON PSO

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2009 International Conference on Machine Learning and Cybernetics(2009机器学习与控制论国际会议)

作者： TIE-JUN ZHOU JIA LI YANG LI School of Computer and Communication Hunan University Changsha 410082 China Computer Science College Central South University of Forestry and Technology Changsha 410004 Chi

Intrusion detection plays more important role in network security today. This paper introduces a method, particle swarm optimization and support vector machine, to intrusion detection system, and presents a new design of ID Based on particle swarm optimization and Support Vector Machine. This paper presents an optimal selection approach of the SVM parameters(regulation parameter C and the radial basis function width parameter σ ) based on particle swarm optimization algorithm. The experiments show that the optimal parameter selection approach based on PSO is available and the Research of Intrusion Detection Based on particle swarm optimization and Support Vector Machine is effective in reducing the number of alerts, false positive, false negative better.

关键词： Intrusion detection particle swarm optimization algorithm Support vector machine Parameter optimization

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Fault Diagnosis for Embedded System Based on Neural Network

Fault Diagnosis for Embedded System Based on Neural Network

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2015 International Conference on Advanced Educational Technology and Information Engineering(AETIE 2015)

作者： G.C.Du Yellow River Conservancy Technical Institute

In the paper, Radial Basis Function(RBF) neural network optimized by particle swarm optimization algorithm is proposed to fault diagnosis for embedded system. The parameters of Radial Basis Function(RBF) neural network are selected by particle swarm optimization algorithm to solve the problem of the parameters selection of Radial Basis Function(RBF) neural network. In order to testify the superiority of Radial Basis Function(RBF) neural network optimized by particle swarm optimization algorithm in fault diagnosis for embedded system, traditional Radial Basis Function(RBF) neural network and Back Propagation(BP) neural network are applied to compare with the proposed Radial Basis Function(RBF) neural network optimized by particle swarm optimization algorithm. The comparison results show that the diagnosis accuracy of Radial Basis Function(RBF) neural network optimized by particle swarm optimization algorithm is the best methods among traditional Radial Basis Function(RBF) neural network, Back Propagation(BP) neural network and Radial Basis Function(RBF) neural network optimized by particle swarm optimization algorithm.

关键词： embedded system RBF neural network fault diagnosis particle swarm optimization algorithm

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Optimal Configuration of Micro-grids Power Supply Based on Operating Modes

Optimal Configuration of Micro-grids Power Supply Based on O...

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2016 IEEE International Conference on Power and Renewable Energy （ICPRE 2016）

作者： Lei Bin Yu Xueying Li Huaqiang Sichuan Electric Power Corporation Power Economic Research Institute Sichuan University

The reasonable capacity configuration of distributed generation in a micro-grid is the prerequisite of its reliable and economical operation. This paper establishes a optimal configuration model of micro grid power supply aiming to reach the goal of the optimal comprehensive benefits of micro grid, and then solve the configuration model by using particle swarm optimization algorithm.

关键词： micro-grid comprehensive benefits power supply optimal configuration particle swarm optimization algorithm

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An Energy-Efficient Operation Approach Based on the Utilization of Regenerative Braking Energy among Trains

An Energy-Efficient Operation Approach Based on the Utilizat...

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International IEEE Conference on Intelligent Transportation Systems

作者： Erchao Chen Bing Bu Wenzhe Sun State Key Lab. of Rail Traffic Control & Safety Beijing Jiaotong Univ. Beijing China

ISBN: (纸本)9781467365970

With the rapid development of urban rail transit, the problem of energy consumption is drawing more and more attentions. Based on the utilization of regenerative braking energy among trains, this paper studies the energy-efficient operation method. We propose an utilization strategy of regenerative energy among trains. Based on the proposed strategy, we set up the energy-saving model which optimizes the timetable and speed profile of trains simultaneously. Based on the particle swarm optimization algorithm, taking Beijing Yizhuang subway line and Changping subway line as examples of short section and long section for simulation, we verify the effectiveness of the proposed method. It is showed that the energy consumption of Yizhuang line and Changping line can be reduced by 3.2% and 5.5%, respectively, through improving the utilization of regenerative energy.

关键词： energy conservation particle swarm optimisation railway electrification regenerative braking energy consumption energy-efficient operation approach particle swarm optimization algorithm regenerative braking energy urban rail transit Acceleration Brakes Energy consumption Linear programming Power supplies Public transportation Rails

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A New Two-stages PSO algorithm for Railway Trajectory Planning on GIS System

A New Two-stages PSO Algorithm for Railway Trajectory Planni...

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IEEE International Conference on Intelligent Transportation Systems

作者： Jun Liu Tianyun Shi Inst. of Comput. Technol. Beijing China

ISBN: (纸本)9781479960798

Smart railway trajectory planning is one of the most interesting and important topics in the fields of intelligent railway transportation, computer science and evolutionary computation, etc. Several objectives and constraints of railway trajectory planning problem are closely related to the distance factor, the construction cost, the altitude factor and the comfortability, etc. More importantly, the new particle swarm optimization (PSO) algorithm, including two optimization sub-stages, firstly optimize the coordinate in y-axis and secondly optimize the latitude in z-axis to design the optimal 3-D railway trajectory. Numerical results highlight that the new two-stages PSO algorithm can provide one realistic optimal trajectory from any two cities in the complicated three-dimensional GIS scenario, such as Chang Sha city and Nan Chang city.

关键词： evolutionary computation geographic information systems particle swarm optimisation railway engineering Chang Sha city GIS system Nan Chang city altitude factor computer science construction cost distance factor intelligent railway transportation optimal 3D railway trajectory optimal trajectory particle swarm optimization algorithm railway trajectory planning problem smart railway trajectory planning three-dimensional GIS scenario two-stages PSO algorithm algorithm design and analysis Cities and towns Linear programming Planning Rail transportation Trajectory evolutionary algorithm Rail transportation algorithm design and analysis Railway engineering Cities and towns geographic information systems Construction costs particle swarm optimization trajectory Distance factor computer science linear programming trajectory planning railways

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Path planning for unmanned vehicle searching based on sensor deployment and travelling salesman problem

Path planning for unmanned vehicle searching based on sensor...

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2014中国制导、导航与控制学术会议

作者： Bin Di Rui Zhou Yu Zhang Jun Che Science and Technology on Aircraft Control Laboratory Beihang UniversityBeijing100191 China AVIC Automatic Flight Control Research InstituteXi''an 710065 China

ISBN: (纸本)9781479946983

The path planning problem for unmanned vehicle searching over the region of interest with obstacles is investigated in this *** path planning problem is decomposed into the sensor deployment problem and the travelling salesman problem based on the fundamental finding that the vehicle could search the region that covered by the sensor if the vehicle pass through the position where the sensor is *** positions of the sensors deployed to cover the region completely are obtained by solving the sensor deployment *** the positions of the deployed sensors as the waypoints that the vehicle has to travel through,the shortest path connecting all the waypoints can be obtained by solving the travelling salesman *** cooperatively coevolving particle swarm optimization algorithm with multiple update rules is newly developed for the sensor deployment *** simulation results demonstrate the feasibility of the proposed methods.

关键词： mobile robots particle swarm optimisation path planning remotely operated vehicles sensor placement travelling salesman problems particle swarm optimization algorithm sensor deployment travelling salesman problem unmanned vehicle optimization particle swarm optimization Path planning Robot sensing systems Search problems Vehicles

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FUZZY CONTROLLER DESIGN AND PARAMETER optimization

FUZZY CONTROLLER DESIGN AND PARAMETER OPTIMIZATION

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2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

作者： WAN-JUN HAO YAN-HUI QIAO WEN-YI QIANG GUO-LIANG LIU School of Astronautics Harbin Institute of Technology Harbin 150001 china School of Computer Bei College of mechanical engineering Beihua University Jilin 132021 China School of Astronautics Harbin Institute of Technology Harbin 150001 china

In this paper, a fuzzy controller with dual controller structure is proposed for solving the contradiction between steady performance and dynamic performance of usual fuzzy controllers. The structure of the obtained controller is simple and its algorithm is convenient, it has good robust and dynamic performance, and can effectively eliminate steady state deviations. For avoiding complex adjustment of parameters as asked for in the design of fuzzy controllers, and attain optimal control properties, a particle swarm optimization (PSO) algorithm has been made use of to optimize the parameters of a fuzzy controller during *** simulations based on typical controlled objects demonstrate the effectiveness and the adaptability of the algorithm, as well as the superiority of the designed controller.

关键词： Fuzzy control Parameter optimizatio particle swarm optimization algorithm

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ADRC Based on Artificial Neural Network for a Six-rotor UAV

ADRC Based on Artificial Neural Network for a Six-rotor UAV

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第40届中国控制会议

作者： Lin Xi Yunfeng Shao Suli Zou Zhongjing Ma Beijing Institute of Technology Lvliang power supply company of Shanxi Electric Power Company

An on-line intelligent optimization method based on an artificial neural network is proposed for the parameter adjustment of the active disturbance rejection controller. And a cascaded ADRC controller including the artificial neural network attitude ADRC is investigated for trajectory tracking of the six-rotor UAV. First, establish the kinematics and dynamics model of the six-rotor, and design a cascaded active disturbance rejection controller for the six-rotor to deal with the non-linear disturbance problem in flight. Secondly, an artificial neural network is designed to optimize the parameters of the attitude ADRC controller on-line, and the particle swarm algorithm is used to set the initial value of the artificial neural network. Finally, the simulation results demonstrated that ADRC based on the artificial neural network can effectively resist the disturbances and enhance the robustness of the attitude controller and the cascade ADRC controller based on the artificial neural network can track the reference trajectory quickly and accurately.

关键词： active disturbance rejection control particle swarm optimization algorithm artificial neural network

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Research on Tennis Recognition Technology Based on Computer Vision

Research on Tennis Recognition Technology Based on Computer ...

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2021 International Conference On Electronics, Circuits And Information Engineering(2021年电子、电路与信息工程国际会议)

作者： Zhang Lu Information Engineering University Luoyang Henan China 471003

ISBN: (纸本)9781665448109

Visual attention mechanism is one of the important means for human beings to perceive the external *** mathematical models to introduce visual attention mechanism into computer vision to simulate human visual perception system is a hot research topic in the field of computer *** research of visual attention model is not only helpful for human beings to better explore the working mechanism of human visual attention,but also has very important significance for solving large-scale data screening and improving image processing efficiency,which has important application value in moving object detection,machine vision,image information matching,image compression and other *** visual attention model is used to preprocess the video sequence,and the region of interest is found as the candidate region for target *** the color and shape matching algorithm is used to match the candidate *** on tennis video show that the algorithm can recognize the target well when the color and shape of the target are relatively single and the significance in the background is high.

关键词： Visual Attention Vector Processor Moving Target Detection particle swarm optimization algorithm Tennis Recognition Model

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