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Simulation with RBF Neural Network Model for Reservoir Operation Rules

WATER RESOURCES MANAGEMENT 2010年第11期24卷 2597-2610页

作者： Wang, Yi-min Chang, Jian-xia Huang, Qiang Xian Univ Technol Sch Water Resources & Hydroelect Power Xian 710048 Peoples R China

Reservoirs usually have multipurpose, such as flood control, water supply, hydropower and recreation. Deriving reservoirs operation rules are very important because it could help guide operators determine the release. For fulfilling such work, the use of neural network has presented to be a cost-effective technique superior to traditional statistical methods. But their training, usually with back-propagation (BP) algorithm or other gradient algorithms, is often with certain drawbacks. In this paper, a newly developed method, simulation with radial basis function neural network (RBFNN) model is adopted. Exemplars are obtained through a simulation model, and RBF neural network is trained to derive reservoirs operation rules by using particle swarm optimization (PSO) algorithm. The Yellow River upstream multi-reservoir system is demonstrated for this study.

关键词： Reservoirs operation rules Simulation with RBF network model particle swarm optimization algorithm

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A New Reliability Prediction Model in Manufacturing Systems

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IEEE TRANSACTIONS ON RELIABILITY 2010年第1期59卷 170-177页

作者： Li, Guo-Dong Masuda, Shiro Yamaguchi, Daisuke Nagai, Masatake Tokyo Metropolitan Univ Dept Syst Design Hino Tokyo 1910065 Japan Kanagawa Univ Dept Engn Yokohama Kanagawa 2218686 Japan

Reliability prediction has been widely studied in many research fields to improve product and system reliability in manufacturing systems. Traditionally, to establish the prediction model, modelers would use all training data without preference. However, the prediction model based only on the most recent data may have better performance. In this paper, to realize an accurate prediction with the most recent data sets, we use the grey model to establish the reliability model. Then, the cubic spline function is integrated into the grey model to enhance the prediction capability of GM(1, 1), a single variable first order grey model. The newly generated model is defined as 3spGM(1, 1). To further improve the prediction accuracy, the particle swarm optimization (PSO) algorithm is applied to 3spGM(1, 1). We call the improved version P-3spGM(1, 1). Finally, we validated the effectiveness of the proposed model using failure data sets of electric product manufacturing systems.

关键词： Cubic spline function grey model particle swarm optimization algorithm reliability prediction model

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Optimizing the Operation of LiNbO₃-Based Multistage Polarization Controllers Through an Adaptive algorithm

IEEE PHOTONICS JOURNAL

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IEEE PHOTONICS JOURNAL 2010年第2期2卷 195-202页

作者： Xi, Lixia Zhang, Xiaoguang Tian, Feng Tang, Xianfeng Weng, Xuan Zhang, Guangyong Li, Xixiang Xiong, Qianjin Beijing Univ Posts & Telecommun Key Lab Informat Photon & Opt Commun Minist Educ Beijing 100876 Peoples R China Huawei Technol Co Ltd Network Res Dept Shenzhen 518129 Peoples R China

The LiNbO3-based polarization controller is widely used, but it needs to be calibrated in order to cancel the remaining birefringence. The calibration of the LiNbO3 polarization controller is untrivial because there are several stages, and for each stage, at least four parameters, including V-A,V-Bias, V-C,V-Bias, V-0, and V-pi, need to be calibrated. A smart calibration approach is presented theoretically and experimentally. The particle swarm optimization (PSO) algorithm is used as an adaptive searching algorithm. The experiment results show that the PSO algorithm is powerful to optimize the operation of LiNbO3-based multistage polarization controllers. It takes only less than 1 min for all the stages of the polarization controller to be thoroughly calibrated.

关键词： LiNbO3 polarization controller optimizing the operation remaining birefringence particle swarm optimization algorithm optical communications

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

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

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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

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Modeling and optimization of HVAC energy consumption

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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

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DNA Word Design Based on Combinational Constraints

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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

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

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

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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

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

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

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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

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

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

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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

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Ecological operation for Three Gorges Reservoir

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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

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