检索结果-内蒙古大学图书馆

Chinese Intelligent Automation Conference (CIAC)

作者： Sun, Zhang Liu, Tao Wang, Jun Luo, Juan Li, Hong Xihua Univ Sch Elect & Informat Engn 999 Jinzhou Rd Chengdu Sichuan Peoples R China

ISBN: (纸本)9783662464694;9783662464687

A particle swarm optimization (PSO) algorithm based on adaptive mutation and P systems is proposed to overcome trapping in local optimum solution and low optimization precision in this paper. The algorithm combines the evolutionary rules of PSO, the strategy of adaptive mutation with the hierarchical membrane structure, and communication rules of P systems. At the same time, in order to achieve rapid economic operation and effectiveness of the micro-grid the proposed algorithm is investigated in experiments which are based on the function optimization of micro-grid's economic operation. Furthermore, the feasibility and effectiveness of the proposed algorithm are shown in the experimental results.

关键词： particle swarm optimization algorithm P systems Function optimization Economic operation

来源：评论

学校读者我要写书评

暂无评论

Study on Network Flow Prediction Model Based on particle swarm optimization algorithm and RBF Neural Network

Study on Network Flow Prediction Model Based on Particle Swa...

引用

2010 3rd IEEE International Conference on Computer Science and Information Technology—ICCSIT 2010

作者： Zhang Yu Bin HeBei Vocational Art College ShiJiaZhuang,China Lin Li Zhong ShiJiaZhuang College ShiJiaZhuang ,China Zhang Ya Ming ShiJiaZhuang Information Engineering Vocational College ShiJiaZhuang,China

It is significant to control network congestion by time series forecasting research for network flow. The hybrid method of particle swarm optimization algorithm and RBF neural network is applied to predict network flow and gain the desirable network flow prediction results. In the hybrid method, particle swarm optimization algorithm is selected and adjusted to the connection weights and the center of radial basis function and the width of radial basis function. The network flow data are collected to search the prediction ability of particle swarm optimization algorithm and RBF neural network. Compared with the results of RBF neural network and BP neural network, particle swarm optimization algorithm and RBF neural network has better forecasting performance.

关键词： network flow neural network particle swarm optimization algorithm prediction model

来源：评论

学校读者我要写书评

暂无评论

swarm Intelligence algorithm for Job Scheduling in Computational Grid 7

Swarm Intelligence Algorithm for Job Scheduling in Computati...

引用

7th International Conference on Intelligent Systems, Modelling and Simulation (ISMS)

作者： Effatparvar, Mehdi Aghayi, Somayeh Asadzadeh, Vahid Dashti, Yosef Islamic Azad Univ Ardabil Branch Dept Comp Ardebil Iran Islamic Azad Univ Ardabil Branch Sama Tech & Vocat Training Coll Ardebil Iran Islamic Azad Univ Germi Branch Dept Comp Germi Iran

ISBN: (纸本)9781509006656

Grid computing is actually the next generation of distributed systems. Its objective is to create a powerful, large and autonomous virtual computer. This computer is created through assembling countless heterogeneous resources with the aim of sharing them. Scheduling is one of the most important and challenging issue of such systems. An accurate and efficient schedule is required to increase the grid efficiency. Grid resources belong to different management domains;each one applies different management policies. This paper proposed a new heuristic approach based on particle swarm optimization algorithm in order to scheduling the jobs in gird environment. The proposed algorithm would create an optimal scheduler to complete the jobs in the minimum flowtime and makespan.

关键词： Job Scheduling Computational Grid particle swarm optimization algorithm Flowtime Makespan

来源：评论

学校读者我要写书评

暂无评论

Frequency Stability of Microgrids Based on H∞ Methods 35

Frequency Stability of Microgrids Based on H∞ Methods

引用

第35届中国控制会议

作者： ZHAO Jian WANG ChaoLi School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology

ISBN: (纸本)9781509009107

The widespread use of renewable energy in microgrid power systems would cause frequency *** in this work,is the frequency stability of the microgrid consisting of wind power systems,photovoltaic systems,micro-turbines,electrolyzers and fuel cells with the variation of load power.A novel robust controller is designed for the microgrid to suppress frequency fluctuation by tuning the output of the micro-turbine,electrolyzer and fuel *** generation-rate constraint of the micro-turbine is *** integrating the switching states of the fuel cell and electrolyzer with the micro-turbine power output in order to prevent too large changing rate of the micro-turbine power and improve the utilization of renewable *** is well known that the key point of design a H∞ mixed sensitivity controller is how to select appropriate weighting ***,there are no effective rules to do *** this reason,the particle swarm optimization（PSO） algorithm is used to optimize the weighting functions to enable the system to achieve optimal *** results show that the mentioned frequency control strategy can effectively stabilize the frequency fluctuation and improve the utilization of renewable energy,and is still effective for the case of large-scale renewable energy penetration.

关键词： microgrid frequency control H∞ control particle swarm optimization algorithm weighting functions

来源：评论

学校读者我要写书评

暂无评论

optimization and CONTROL of a HEV

Optimization and CONTROL of a HEV

引用

International Conference on Electrical, Electronics, and optimization Techniques (ICEEOT)

作者： Farahat, Mohammad Esmaeil Farahat, Said Islamic Azad Univ Aliabad Katoul Branch Dept Elect Engn Aliabad Katoul Iran Univ Sistan & Baluchestan Dept Mech Engn Zahedan Iran

ISBN: (纸本)9781467399395

Vehicles play an important role in transportation. Using fossil fuels as their source of energy, they are a source of pollution. HEVs are improving and a day will come that they will take over the role of conventional vehicles. In the path of improving HEVs, optimizing components sizes of the vehicle and better strategy controls are vital methods to reach the desired goals. In this path practical tools for optimization are evolutionary algorithms and fuzzy controllers as a strategy control decision maker. In this paper, accompanied with these tools extraordinary improvements are made. On the UDDS cycle using PSO algorithm we reached 57%, 68%, 34% and 8% decrease respectively in fuel consumption, emission, economic and acceleration and we reached 30% increase in maximum speed gained. On the HWFET cycle we reached 74%, 79%, 34% and 8% decrease respectively in fuel consumption, emission, economic and acceleration and we reached 30% increase in maximum speed gained. Acquiring a Pareto Front for two fitness functions we can choose a specific vehicle with special capabilities according to our priorities.

关键词： Hybrid vehicles particle swarm optimization algorithm power management strategy sizing drive cycle

来源：评论

学校读者我要写书评

暂无评论

Short-Term Traffic Flow Prediction Method Based on Grey Adaptive particle swarm Support Vector Machine 2

Short-Term Traffic Flow Prediction Method Based on Grey Adap...

引用

2nd IEEE International Conference on Computer and Communications (ICCC)

作者： Duo, Mei Xu, E. Qi, Yan Bohai Univ Coll Informat Sci & Technol Jinzhou Peoples R China

ISBN: (纸本)9781467390262

In order to further improve the accuracy of the short-term traffic flow prediction, a combination of short-term traffic flow prediction model had been proposed by analyzing the characteristics of grey model, adaptive particle swarm optimization (PSO) algorithm and support vector machine (SVM) model. First, use the grey model to accumulate the original traffic flow data, weaken the randomness of the traffic flow data sequence, then optimize the support vector machine model based on adaptive particle swarm optimization algorithm and realize short-term traffic flow prediction, finally, get the final predicted value table by grey mode. The model was verified based on the traffic flow data of the major road in Changchun and the experimental result showed the proposed model was effective and feasible.

关键词： traffic flow prediction grey model particle swarm optimization algorithm support vector machine

来源：评论

学校读者我要写书评

暂无评论

Optimal location and sizing of STATCOM using Fuzzy-PSO approach 6

Optimal location and sizing of STATCOM using Fuzzy-PSO appro...

引用

6th IEEE International Conference on Power Systems (ICPS)

作者： Rana, Bharat Singh Srivastava, Laxmi Madhav Inst Sci & Technol Dept Elect Engn Gwalior India

ISBN: (纸本)9781509001286

In this paper, an evolutionary computing technique comprising of Fuzzy logic and particle swarm optimization (PSO) algorithm has been proposed for optimal location and sizing of STATCOM to improve the voltage stability and to minimize the total voltage deviation in a power system. The proposed Fuzzy-PSO algorithm has been applied using two steps. As the first step, the weakest buses selected for placement of STATCOM using modal analysis. In the second step Fuzzy-PSO algorithm has been applied for selecting optimal location of STATCOM considering these selected weakest buses. The proposed approach has been applied on the standard IEEE 30-bus system considering the most severe single line outage contingencies under normal loading and under stressed condition. The proposed Fuzzy-PSO approach has been found to be quite satisfactory.

关键词： fuzzy performance index modal analysis particle swarm optimization algorithm STATCOM voltage stability

来源：评论

学校读者我要写书评

暂无评论

A Design Method of Zero Ripple Input Current DC-DC Converter Assisted by Constrained GA&PSO algorithms to Minimize Power Losses 19

A Design Method of Zero Ripple Input Current DC-DC Converter...

引用

19th International Conference on Electrical Machines and Systems (ICEMS)

作者： Marsala, Giuseppe Ragusa, Antonella CNR ISSIA UOS Palermo Italy

ISBN: (纸本)9784886860989

The paper presents a constrained optimization procedure to design a DC-DC converter with coupled inductors for minimizing the power losses. Two algorithms have been used, Genetic and particle swarm optimization algorithm, and the results have been compared. In particular, with the proposed technique, the electrical, magnetic and geometrical characteristics of the coupled inductors have been obtained and the values of duty cycle and frequency have been defined in order to obtain the maximum efficiency.

关键词： DC-DC converter Genetic algorithm particle swarm optimization algorithm power losses

来源：评论

学校读者我要写书评

暂无评论

Solving a multi-stage multi-product solid supply chain network design problem by meta-heuristics

引用

SCIENTIA IRANICA 2016年第3期23卷 1429-1440页

作者： Mahmoodirad, A. Sanei, M. Islamic Azad Univ Cent Tehran Branch Dept Math Tehran Iran

This paper presents an effective optimization method based on meta-heuristics algorithms for the design of a multi-stage, multi-product solid supply chain network design problem. First, a mixed integer linear programming model is proposed. Second, because the problem is an NP-hard, three meta-heuristics algorithms, namely Differential Evolution (DE), particle swarm optimization (PSO), and Gravitational Search algorithm (GSA), are developed for the first time for this kind of problem. To the best of our knowledge, neither DE, nor PSO, nor GSA have been considered for the multi-stage solid supply chain network design problems. Furthermore, the Taguchi experimental design method is used to adjust the parameters and operators of the proposed algorithms. Finally, to evaluate the impact of increasing the problem size on the performance of our proposed algorithms, different problem sizes are applied and the associated results are compared with each other. (C) 2016 Sharif University of Technology. All rights reserved.

关键词： Supply chain network design Differential evolution particle swarm optimization algorithm Gravitational search algorithm Taguchi experimental Design

来源：评论

学校读者我要写书评

暂无评论

Optimizing Thermal-Elastic Properties of C/C-SiC Composites Using a Hybrid Approach and PSO algorithm

引用

MATERIALS 2016年第4期9卷 222-222页

作者： Xu, Yingjie Gao, Tian Northwestern Polytech Univ ESAC Xian 710072 Peoples R China

Carbon fiber-reinforced multi-layered pyrocarbon-silicon carbide matrix (C/C-SiC) composites are widely used in aerospace structures. The complicated spatial architecture and material heterogeneity of C/C-SiC composites constitute the challenge for tailoring their properties. Thus, discovering the intrinsic relations between the properties and the microstructures and sequentially optimizing the microstructures to obtain composites with the best performances becomes the key for practical applications. The objective of this work is to optimize the thermal-elastic properties of unidirectional C/C-SiC composites by controlling the multi-layered matrix thicknesses. A hybrid approach based on micromechanical modeling and back propagation (BP) neural network is proposed to predict the thermal-elastic properties of composites. Then, a particle swarm optimization (PSO) algorithm is interfaced with this hybrid model to achieve the optimal design for minimizing the coefficient of thermal expansion (CTE) of composites with the constraint of elastic modulus. Numerical examples demonstrate the effectiveness of the proposed hybrid model and optimization method.

关键词： C/C-SiC composites micromechanical modeling BP neural network particle swarm optimization algorithm thermal-elastic properties

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：