检索结果-内蒙古大学图书馆

Time-series prediction using a local linear wavelet neural network

NEUROCOMPUTING 2006年第4-6期69卷 449-465页

作者： Chen, YH Yang, B Dong, JW Jinan Univ Sch Informat Sci & Engn Jinan 250022 Peoples R China Wuhan Univ Sci & Technol State Key Lab Adv Technol Mat Synthesis & Proc Wuhan Peoples R China

A local linear wavelet neural network (LLWNN) is presented in this paper. The difference of the network with conventional wavelet neural network (WNN) is that the connection weights between the hidden layer and output layer of conventional WNN are replaced by a local linear model. A hybrid training algorithm of particle swarm optimization (PSO) with diversity learning and gradient descent method is introduced for training the LLWNN. Simulation results for the prediction of time-series show the feasibility and effectiveness of the proposed method. (c) 2005 Elsevier B.V. All rights reserved.

关键词： local linear wavelet neural networks particle swarm optimization algorithm gradient descent algorithm time-series prediction

来源：评论

学校读者我要写书评

暂无评论

AN IMPROVED particle swarm optimization METHOD BASED ON BORDERLINE SEARCH STRATEGY FOR TRANSMISSION NETWORK EXPANSION PLANNING

AN IMPROVED PARTICLE SWARM OPTIMIZATION METHOD BASED ON BORD...

引用

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

作者： DONG-XIAO NIU YUN-PENG LING QI ZHAO QING-YING ZHAO School of Business and Administration North China Electric Power University Baoding 071002 China

To solve the problem of network expansion, an improved particle swarm optimization algorithm (PSO) is proposed in this paper. This method initialized the particle swarm according to borderline search mind, made the initialized particle near the safety line, overcome the defect of the uncertainty in the rational distribution of particle initialization, optimizing the range of the *** simulation results of power transmission network planning demonstrate the feasibility and efficiency of this method, and shed new light on the further improving of PSO.

关键词： Transmission network expansion planning particle swarm optimization algorithm Borderline search strategy

来源：评论

学校读者我要写书评

暂无评论

Comparison of different modulation formats for polarization mode dispersion compensators

Comparison of different modulation formats for polarization ...

引用

Conference on Optical Transmission, Switching, and Subsystems IV

作者： Wu, Huaiyi Chen, Lin Wen, Shuangchun Hunan Univ Sch Comp & Commun Changsha 410082 Peoples R China

ISBN: (纸本)0819464481

We propose a polarization mode dispersion (PMD) compensation scheme for wavelength-division-multiplexing (WDM) system, in which two WDM channels share one PMD compensator at the receiver site. The effect of different modulation formats on multi-stage PMD compensators is studied and compared by numerical simulations in 40-Gb/s WDM optical fiber communication system. The degree of polarization (DOP) of single state of polarization (SOP) optical signal is used as the feedback signal in PMD compensators. The particle swarm optimization (PSO) algorithm is used as the searching algorithm in WDM systems. The compensated DOP values of return-to-zero (RZ) format and nonreturn-to-zero (NRZ) format by multi-stage PMD compensators have been increased distinctly compared to the corresponding cases without compensation. It is shown that the PSO algorithm is implemented successfully in adaptive multi-stage PMD compensation in a 40-Gb/s optical WDM system. The compensated eye diagrams for the two channels by multi-stage PMD compensators indicate that the three-stage PMD compensator which eliminates the influence of second-order PMD completely in WDM system takes the best efficiency in the multi-stage PMD compensators for RZ format and NRZ format.

关键词： wavelength-division-multiplexing polarization mode dispersion particle swarm optimization algorithm multi-stage PMD compensator degree of polarization RZ format NRZ format

来源：评论

学校读者我要写书评

暂无评论

PMD compensation in WDM system using the worst channel equalization scheme

PMD compensation in WDM system using the worst channel equal...

引用

Conference on Optical Transmission, Switching, and Subsystems IV

作者： Chen, Min Chen, Lin Wen, Shuangchun Hunan Univ Sch Comp & Commun Changsha 410082 Peoples R China

ISBN: (纸本)0819464481

We adopt the worst channel equalization (WCE) scheme to compensate polarization mode dispersion (PMD) in wavelength-division-multiplexing (WDM) systems. The degree of polarization (DOP) of single state of polarization (SOP) optical signal is used as the feedback signal of the PMD compensators, and the particle swarm optimization (PSO) algorithm is used as the searching algorithm. Simulation results show that the DOP of RZ format of the worst-performance channels after compensation is greatly improved, and the PSO algorithm is successfully experienced into adaptive multi-stage PMD compensators in a 40-Gb/s optical WDM communication system. The WCE scheme is an effective way for PMD compensation in WDM system.

关键词： wavelength-division-multiplexing coupled nonlinear Schrodinger equation worst channel equalization polarization mode dispersion particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Fuzzy controller design and parameter optimization

Fuzzy controller design and parameter optimization

引用

5th International Conference on Machine Learning and Cybernetics

作者： Hao, Wan-Jun Qiao, Yan-Hui Liu, Guo-Liang Qiang, Wen-Yi Harbin Inst Technol Sch Astron Harbin 150001 Peoples R China Beihua Univ Coll Mech Engn Jilin 132021 Peoples R China

ISBN: (纸本)1424400600

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 design. Numerical 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 optimization particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

The research on a novel geometric constraint solver

The research on a novel geometric constraint solver

引用

6th World Congress on Intelligent Control and Automation

作者： Cao, Chunhong Zhang, Bin Li, Xiaolin Wang, Limin Li, Wenhui Northeastern Univ Coll Informat Sci & Engn Shenyang 110004 Peoples R China

ISBN: (纸本)1424403316

When transferring the geometric constraint equation group into the optimization model, we need a method to jump out of the local beat solution so that we can find a global best solution. Considering the speed and global capability, we adopt compound particle group optimization algorithm. particle swarm optimization algorithm is a kind of evolution computation technology based on group intelligence. In all the evolution computations heuristic function should be included to control its one's own characteristic. These parameters are usually correlated with the specific problem and are defined by the users. Suitable parameter choice needs user abundant experience and correct judgment on the information offered by the problem. More important thing is that these heuristic parameters will influence the convergence characteristic of the algorithm. Because of this even experienced users may choose the not appropriate parameter and then make the problem unable to get effective solution. It needs to carry on some research on these parameters more and more. Here we choose the control parameters as an optimization question in the particle swarm algorithm. Thus heuristic function in the PSO can be controlled by the ordinal genetic algorithm and we form the composite particle swarm optimization algorithm. And we use this algorithm into the geometric constraint solving successfully.

关键词： geometric constraint solving group intelligent algorithm particle swarm optimization algorithm composite particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

FUZZY CONTROLLER DESIGN AND PARAMETER optimization

FUZZY CONTROLLER DESIGN AND PARAMETER OPTIMIZATION

引用

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

来源：评论

学校读者我要写书评

暂无评论

Exploratory Developemnt of Parameters Identify Based on Reformative PSO algorithm in DTC System

Exploratory Developemnt of Parameters Identify Based on Refo...

引用

第一届国际测量仪器与测试自动化学术会议

作者： Cao Chengzhi Wu YuSheng (Shenyang University of Technology. XingHua Street 110023 China)

＜正＞In order to improve the stability and dependability of the Direct Torque Control （DTC）system in low speed state of asynchronous dynamo.a kind of reformative particle swarm optimization（PSO）algorithm. which optimizes the Wavelet Neural Network（WNN）,is used for observing parameters which contain rev. magnetic likage and stator resistance, insteading of conventional velocity generator and magnetic likage sight. Relativing to the problems, such as easily sinking into the part optimal *** speed in astringency. short exactitude in precision and so on. this reformative method divides the optimize particles into two teams, one of them adopts part particle swarm algorithm which adhibits compressibility factor, the others adopts global particle swarm algorithm which adhibits inertial weighting, both the local value and the global value can be compromised for improving the astringency speed and precision through combining these two teams. At the same time the network can constitute the link between wavelet transform and network quotiety. which is used for observing parameters. Passed by the validate of experimental result, this kind of reformative PSO algorithm which optimal WNN can fast converge, and it has good exactitude in precision. So it can make the asynchronous dynamo keep high capability, especially in low speed state.

关键词： Direct torque control particle swarm optimization algorithm wavelet neural network part optimal value.

来源：评论

学校读者我要写书评

暂无评论

Prediction of concrete material based on PSO algorithm

引用

Jianzhu Jiegou Xuebao/Journal of Building Structures 2006年第SUPPL.期27卷 722-725页

作者： Liang, Benliang Sun, Fuxue State Key Laboratory for Disaster Reduction in Civil Engineering Tongji University Shanghai 200092 China Department of Geotechnical Engineering Tongji University Shanghai 200092 China

Concrete carbonation was affected by several factors. On the basis of this, the BP networks input vectors were constructed. Through the introduction of PSO algorithm, the connection weights of the model can be optimized, overcoming the shortcomings of the inefficiency in terms of convergence and the great possibility being stuck in a local minimum. The computation indicated that the accuracy and convergence velocity processed by this method is much better than that only adopted by BP algorithm.

关键词： Concrete carbonation Durability Neural networks particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

optimization of machining parameters for milling operations using non-conventional methods

引用

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2005年第11-12期25卷 1078-1088页

作者： Baskar, N Asokan, P Prabhaharan, G Saravanan, R SASTRA Sch Mech Engn Thanjavur 613402 Tamil Nadu India Reg Engn Coll Dept Prod Engn Tiruchirappalli 620015 India JJ Coll Engn & Technol Dept Mech Engn Tiruchirappalli 620009 India

In this paper, optimization procedures based on the genetic algorithm, tabu search, ant colony algorithm and particle swarm optimization algorithm were developed for the optimization of machining parameters for milling operation. This paper describes development and utilization of an optimization system, which determines optimum machining parameters for milling operations. An objective function based on maximum profit in milling operation has been used. An example has been presented at the end of the paper to give a clear picture from the application of the system and its efficiency. The results are compared and analysed using the method of feasible directions and handbook recommendations.

关键词： ant colony algorithm genetic algorithm optimization multi-tool milling particle swarm optimization algorithm tabu search algorithm

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：