检索结果-内蒙古大学图书馆

On-line optimization of Chaotic Systems Synchronization Based on Improved particle swarm optimization

On-line Optimization of Chaotic Systems Synchronization Base...

The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

作者： Dong Fenying College of Information Engineering TANYUAN UNIVERSITY of TECHNOLOGY Taiyuan China

ISBN: (纸本)9781424472352

This paper studied the feedback parameter optimization which applies the modified particle swarm optimization to realize chaos systems synchronization. However, the object function to be optimized is a multiple hump function, so, in the paper, the random and the ergodicity of the chaotic sequence were applied to initialize particle populations. Because the chaos system is sensitive to the initial value, two chaos systems with same structures and different initial sates will eventually lead to two different trajectories, even if its output error arbitrarily small, This paper used the rolling horizon principle of predictive control to make online optimization of the chaos systems in order to realize the synchronization. Take the chaos system Lorenz for example, we did the numerical simulation to test the feasibility and effectiveness of chaos systems synchronization based on the improved particle swarm optimization. The results indicate that the convergence rate of the system could be improved by the synchronization of the chaos system based on improved particle swarm optimization, which is of good robustness.

关键词： particle swarm optimization algorithm chaos synchronization chaotic sequence on-line optimization

来源：评论

学校读者我要写书评

暂无评论

Modeling and optimization of HVAC energy consumption

引用

APPLIED ENERGY 2010年第10期87卷 3092-3102页

作者： Kusiak, Andrew Li, Mingyang Tang, Fan Univ Iowa Dept Mech & Ind Engn Iowa City IA 52242 USA

A data-driven approach for minimization of the energy to air condition a typical office-type facility is presented. Eight data-mining algorithms are applied to model the nonlinear relationship among energy consumption, control settings (supply air temperature and supply air static pressure), and a set of uncontrollable parameters. The multiple-linear perceptron (MLP) ensemble outperforms other models tested in this research, and therefore it is selected to model a chiller, a pump, a fan. and a reheat device. These four models are integrated into an energy optimization model with two decision variables, the set-point of the supply air temperature and the static pressure in the air handling unit. The model is solved with a particle swarm optimization algorithm. The optimization results have demonstrated the total energy consumed by the heating, ventilation, and air-conditioning system is reduced by over 7%. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： HVAC optimization Data mining Neural network ensemble Energy saving particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

DNA Word Design Based on Combinational Constraints

引用

JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE 2010年第10期7卷 1973-1977页

作者： Zhang, Qiang Zhang, Rui Dalian Univ Technol Minist Educ Key Lab Adv Design & Intelligent Comp Dalian 116622 Peoples R China

The design of DNA code words has been proved to be an important problem for bimolecular computing. It plays an important role in improving the reliability and the scale of DNA computing. Recent experimental and theoretical advances have produced and tested new methods to obtain large DNA word sets to support virtually any kind of applications. In this paper, we use particle swarm optimization algorithm (PSO) to design DNA word sets with H-distance and Hamming distance combinatorial constraints. By comparing our experimental results with the previous works, our results improve the lower bounds which satisfy combinational constraints, and further shorten the value range of DNA coding bounds. In our computational experiments, we succeed in generating better DNA word sets and give some practical values which satisfy H-distance and Hamming distance constraints. To the best of our knowledge, these results are obtained for the first time, which provide direction for the research of theoretical bounds in DNA coding and the bounds of 4-ary in coding theory.

关键词： DNA Word particle swarm optimization algorithm Combinational Constraints

来源：评论

学校读者我要写书评

暂无评论

The Scheduling algorithm of Grid Task Based on PSO and Cloud Model

The Scheduling Algorithm of Grid Task Based on PSO and Cloud...

引用

International Conference on Advanced Measurement and Test (AMT 2010)

作者： Zhong Shaobo He Zhongshi Chongqing Normal Univ Coll Elementary Educ Chongqing Peoples R China Chongqing Res Ctr Elementary Teacher Educ Chongqing Peoples R China Chongqing Univ Coll Comp Sci Chongqing 400044 Peoples R China

ISBN: (纸本)0878492712

Grid task scheduling (GTS) is a NP-hard problem. This paper proposes an optimized GTS algorithm which combines with the advantages of cloud model based on the particle swarm optimization algorithm. This algorithm iterates tasks utilizing the advantages of particle swarm optimization algorithm and then gets a set of candidate solutions quickly. In addition, this algorithm modifies the value of entropy and excess entropy using the characteristics of cloud model and implements the transformation between qualitative variables and quantity of uncertain events. And this algorithm makes particles fly to the global optimal solutions by exact searching in local areas. Theoretical analysis and simulation results show that this algorithm makes load balance of resource efficiently. It also avoids the problems of genetic algorithm and basic particle swarm optimization algorithm, which would easily fall into local optimal solutions and premature convergence caused by too much selected pressure. This algorithm has the advantages of high precision and faster convergence and can be applied in task scheduling on computing grid.

关键词： grid computing task scheduling cloud model particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Solving Pressure Vessel Design Problems by an Effective Global Harmony Search algorithm

Solving Pressure Vessel Design Problems by an Effective Glob...

引用

22nd Chinese Control and Decision Conference

作者： Gao, Liqun Zou, Dexuan Ge, Yanfeng Jin, Wenjing Northeastern Univ Sch Informat Sci & Engn Shenyang 110004 Peoples R China

ISBN: (纸本)9781424451821

We use an effective global harmony search algorithm (EGHS) to solve two kinds of pressure vessel design problems. In general, the two problems are formulated as mixed-integer non-linear programming problems with several constraints. The EGHS combines harmony search algorithm (HS) with concepts from the swarm intelligence of particle swarm optimization algorithm (PSO) to solve the two optimization problems. The EGHS algorithm has been applied to two typical problems with results better than previously reported. The results have demonstrated that the EGHS has strong convergence and capacity of space exploration on solving pressure vessel design problems.

关键词： Effective global harmony search algorithm Pressure vessel design Harmony search algorithm particle swarm optimization algorithm Convergence

来源：评论

学校读者我要写书评

暂无评论

Comparing PSO and NSGA II for the Biobjective Oil Derivatives Distribution Problem

Comparing PSO and NSGA II for the Biobjective Oil Derivative...

引用

2010 IEEE World Congress on Computational Intelligence

作者： de Souza, Thatiana C. N. Goldbarg, Elizabeth F. G. Goldbarg, Marco C. Univ Fed Rio Grande do Norte BR-59072970 Natal RN Brazil Univ Fed Rio Grande do Norte Dept Informat & Appl Mat Natal RN Brazil

ISBN: (纸本)9781424481262

This paper presents an experimental analysis of three algorithms for the Oil Derivatives Distribution Problem with two objectives. The problem consists in scheduling the transmission of oil products from source nodes to terminals in due times. The minimization of two objectives is considered: delivery time and fragmentation, that is, the consecutive transmission of distinct products in the same polyduct. The performance of a particle swarm optimization algorithm is compared to the performance of two versions of the NSGA II algorithm in a set of 15 instances. The results show that the particle swarm algorithm outperforms the NSGA II.

关键词： NSGA II algorithm PSO biobjective oil derivatives distribution problem delivery time experimental analysis fragmentation genetic algorithms minimisation minimization oil products transmission particle swarm optimisation particle swarm optimization algorithm petroleum industry scheduling scheduling source nodes

来源：评论

学校读者我要写书评

暂无评论

Ecological operation for Three Gorges Reservoir

引用

Water Science and Engineering 2011年第2期000卷

作者： Wen-xian GUO Hong-xiang WANG Jian-xin XU Zi-qiang XIA North China University of Water Conservancy and Electric Power Zhengzhou 450011 P R. China State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering Hohai University Nanjing 210098 P. R. China

The traditional operation of the Three Gorges Reservoir has mainly focused on water for flood control, power generation, navigation, water supply, and recreation, and given less attention to the negative impacts of reservoir operation on the river ecosystem. In order to reduce the negative influence of reservoir operation, ecological operation of the reservoir should be studied with a focus on maintaining a healthy river ecosystem. This study considered ecological operation targets, including maintaining the river environmental flow and protecting the spawning and reproduction of the Chinese sturgeon and four major Chinese carps. Using flow data from 1900 to 2006 at the Yichang gauging station as the control station data for the Yangtze River, the minimal and optimal river environmental flows were analyzed, and eco-hydrological targets for the Chinese sturgeon and four major Chinese carps in the Yangtze River were calculated. This paper proposes a reservoir ecological operation model, which comprehensively considers flood control, power generation,navigation, and the ecological environment. Three typical periods, wet, normal, and dry years, were selected, and the particle swarm optimization algorithm was used to analyze the model. The results show that ecological operation modes have different effects on the economic benefit of the hydropower station, and the reservoir ecological operation model can simulate the flood pulse for the requirements of spawning of the Chinese sturgeon and four major Chinese carps. According to the results, by adopting a suitable re-operation scheme, the hydropower benefit of the reservoir will not decrease dramatically while the ecological demand is met. The results provide a reference for designing reasonable operation schemes for the Three Gorges Reservoir.

关键词： ecological operation environmental flow Three Gorges Reservoir particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Generate and Optimize Fuzzy Rules Using the particle swarm algorithm

Generate and Optimize Fuzzy Rules Using the Particle Swarm A...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Esmin, A. A. A. Lambert-Torres, G. Univ Fed Lavras DCC UFLA Dept Comp Sci BR-37200000 Lavras MG Brazil

ISBN: (纸本)9781424465880

The success of fuzzy application to solve the control problems depends on a number of parameters, such as fuzzy rules and membership functions. The problem of generating desirable fuzzy rules is very important in the development of fuzzy systems, which are usually decided upon subjectively. This paper describes a very simple and straightforward fuzzy rule generation and optimization technique by using the particle swarm optimization algorithm (PSO). The proposed algorithm can obtain a set of fuzzy rules which cover the examples set in iterative process. The proposed method is tested with promising results.

关键词： PSO algorithm control problems fuzzy control fuzzy rules optimization fuzzy systems membership function particle swarm optimisation particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Application and Comparison of Several Intelligent algorithms on Muskingum Routing Model

Application and Comparison of Several Intelligent Algorithms...

引用

2nd IEEE International Conference on Information and Financial Engineering (ICIFE)

作者： Yang Zhengxiang Kang Ling Huazhong Univ Sci & Technol Digital Engn & Simulat Res Ctr Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Sch Hydropower & Informat Engn Wuhan 430074 Hubei Peoples R China

ISBN: (纸本)9781424469284

In order to solve the problem of linearization, complexity and poor accuracy for parameter estimate of Muskingum Routing Model at present, this paper introduces three modern intelligent algorithms - Genetic algorithm (GA), Simulated Annealing algorithm (SA) and particle swarm optimization algorithm (PSO) for the parameter calibration of Muskingum model. Through specific simulation, the results of five methods are produced. Then according to the calculation, comparison and analysis of five methods comprehensively, it is found that the results of three modern intelligent algorithms are fit significantly and better than traditional methods.

关键词： Muskingum Model Genetic algorithm Simulated Annealing algorithm particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Hybrid particle swarm and Neural Network Approach for Streamflow Forecasting

Hybrid Particle Swarm and Neural Network Approach for Stream...

引用

9th International Conference on Numerical Analysis and optimization

作者： Sedki, A. Ouazar, D. Univ Mohammed V Agdal Mohammadia Sch Engn Dept Civil Engn Rabat Morocco

In this paper, an artificial neural network (ANN) based on hybrid algorithm combining particle swarm optimization (PSO) with back-propagation (BP) is proposed to forecast the daily streamflows in a catchment located in a semi-arid region in Morocco. The PSO algorithm has a rapid convergence during the initial stages of a global search, while the BP algorithm can achieve faster convergent speed around the global optimum. By combining the PSO with the BP, the hybrid algorithm referred to as BP-PSO algorithm is presented in this paper. To evaluate the performance of the hybrid algorithm, BP neural network is also involved for a comparison purposes. The results show that the neural network model evolved by PSO-BP algorithm has a good predictions and better convergence performances.

关键词： artificial neural network particle swarm optimization algorithm back propagation daily streamflows catchment semi-arid climate

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：