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International Conference on Electrical Machines and Systems

作者： Giuseppe Marsala Antonella Ragusa I.S.S.I.A - C.N.R. U.O.S. Palermo- Italy

ISBN: (纸本)9781467388634

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

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Performance of A Circular Crossed-Dipole Array for SDMA Configuration Adopting Directivity and Polarization Control Using particle swarm optimization algorithm

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INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING 2009年第1期19卷 50-59页

作者： Mahmoud, K. R. Bansal, R. El-Adawy, M. I. Zainud-Deen, S. H. Ibrahem, Sabry M. M. Helwan Univ Fac Engn Dept Elect Commun & Comp Cairo Egypt Univ Connecticut Dept Elect & Comp Engn Storrs CT USA Menoufia Univ Fac Elect Engn Dept Elect & Elect Commun Engn Menoufia Egypt

In this article, the performance of a circular crossed-dipole array (CCDA) for space division multiple access (SDMA) configurations adopting directivity and polarization control is presented. The array consists of 12 dual-polarized elements uniformly distributed in a circular configuration;each dual-polarized element (crossed-dipole) consists of two half-wave dipoles in a +/- 45 degrees slant configuration. The modified particle swarm optimization and moment of method (MPSO-MOM) algorithm is used to calculate the complex weightings of the array elements in a mutual coupling environment for beamforming synthesis. In addition, the performance of the adaptive array using discrete feedings (1-bit amplitude and 4-bit phase shifters or only 4-bit phase shifters) is studied. (C) 2008 Wiley Periodicals, Inc. Int J RF bind Microwave CAE 19: 50-59. 2009.

关键词： smart antennas adaptive beamforming crossed-dipole antenna uniform circular arrays method of moments particle swarm optimization algorithm

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DNA SEQUENCE SETS DESIGN BY particle swarm optimization algorithm

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INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL 2009年第8期5卷 2249-2255页

作者： Zhang, Qiang Zhang, Rui Wang, Bin Dalian Univ Liaoning Key Lab Intelligent Informat Proc Dalian 116622 Peoples R China

Designing DNA sequence sets is a fundamental issue in the fields of nanotechnology and nanocomputing. Not only quality but also quantity of DNA coding sequences affect the reliability of DNA computing. For this reason, many researchers have paid their attentions to find more and better DNA sequences in DNA computing. In this paper we present particle swarm optimization algorithm (PSO) for the design of DNA sequence sets, namely sets of equal-length sequence over the nucleotides alphabet A,C,G,T that satisfy H-distance constraint. In our computational experiments, we succeed in generating better sequences sets. We give some practical values which satisfy H-distance constraint, and it has some directions for the theoretical lower bound in DNA computing.

关键词： DNA sequence sets particle swarm optimization algorithm H-distance

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Joint Multiuser And Inter-symbol Interference Suppression In CDMA Systems Using particle swarm optimization algorithms

Joint Multiuser And Inter-symbol Interference Suppression In...

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21st Iranian Conference on Electrical Engineering (ICEE)

作者： Arani, Atefeh Haji Jamali Azmi, Paeiz Tarbiat Modares Univ Tehran Iran

ISBN: (纸本)9781467356343

Using particle swarm optimization (PSO) has become a common heuristic technique in many fields of engineering. In this paper, we apply PSO to solve Joint Multiuser and Inter-symbol Interference (ISI) Suppression problems in the code-division multiple-access (CDMA) systems over multipath Rayleigh fading channel, to reduce the computational complexity. In the proposed method, conventional detector (CD) is used as the first stage to initialize the PSO algorithm and time-varying acceleration coefficients (TVAC) are used in PSO algorithm. The simulation results show that the performance of PSO-based MUD with TVAC is promising and outperform the CD.

关键词： Code division multiple access particle swarm optimization algorithm multiple access interference Inter-symbol Interference multiuser detection

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Research on a Distribution Center Location Model Based on a particle swarm optimization algorithm

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International Journal of Plant Engineering and Management 2009年第3期14卷 151-157页

作者： WANG Fei 1,2,HU Xin-bu3,JIA Tao41 School of Economy and Management,Chang’an University,Xi’an 710064,P.R.China 2 Institute of Human Geography,Xi’an International Studies University,Xi’an 710061,P.R.China 3 Architecture Engineering Department,Engineering College of Armed Police Forces,Xi’an 710086,P.R.China 4 School of Management,Xi’an Jiaotong University,Xi’an 710069,P.R.China School of Economy and Management Chang'an UniversityXi'an 710064P.R.China Institute of Human Geography Xi'an International Studies UniversityXi'an 710061P.R.China Architecture Engineering Department Engineering College of Armed Police ForcesXi'an 710086P.R.China School of Management Xi'an Jiaotong UniversityXi'an 710069P.R.China

Logistics is supposed to be the important source of profits for the enterprises besides reducing material consumption and improving labor productivity. Transportation costs, distribution center construction costs, ordering costs, safe inventory costs and inventory holding costs are the important parts of the total logistics costs. In this paper, based on the research results of LMRP（ location model of risk pooling） location with fixed construction cost, the LMRPVCC （ location model of risk pooling based on variable construction cost） will be introduced. Applying particle swarm optimization to several computational instances, the authors find the suboptimum solution of the model.

关键词： location-inventory particle swarm optimization algorithm variable cost of construction

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Assimilation of Two Variables Derived from Hyperspectral Data into the DSSAT-CERES Model for Grain Yield and Quality Estimation

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REMOTE SENSING 2015年第9期7卷 12400-12418页

作者： Li, Zhenhai Wang, Jihua Xu, Xingang Zhao, Chunjiang Jin, Xiuliang Yang, Guijun Feng, Haikuan Beijing Acad Agr & Forestry Sci Beijing Res Ctr Informat Technol Agr Beijing 100097 Peoples R China Natl Engn Res Ctr Informat Technol Agr Beijing 100097 Peoples R China Zhejiang Univ Inst Agr Remote Sensing & Informat Applicat Hangzhou 310029 Zhejiang Peoples R China Beijing Acad Agr & Forestry Sci Beijing Res Ctr Agr Stand & Testing Beijing 100097 Peoples R China Minist Agr Key Lab Informat Technol Agr Beijing 10097 Peoples R China Beijing Engn Res Ctr Agr Internet Things Beijing 100097 Peoples R China Chinese Acad Sci Northeast Inst Geog & Agroecol Key Lab Wetland Ecol & Environm Changchun 130102 Peoples R China

The combination of remote sensing and crop growth models has become an effective tool for yield estimation and a potential method for grain quality estimation. In this study, two assimilation variables (derived from a hyperspectral sensor), called leaf area index (LAI) and canopy nitrogen accumulation (CNA), were jointly used to calibrate the sensitive parameters and initial states of the DSSAT-CERES crop model, to improve simulated output of the grain yield and protein content of winter wheat. The results show that the modified simple ratio (MSR) and normalized difference red edge (NDRE) better estimated LAI and CNA, respectively, compared with the other possible vegetation indices. The integration of both LAI and CNA resulted in a more robust DSSAT-CERES models with than each one alone. The R-2 and RMSE values, respectively, of the regression between the simulated (using the two assimilation variables method) and measured LAI were 0.828 and 0.494, and for CNA were 0.808 and 20.26 kg ***(-1). These two assimilation variables resulted in grain yield and protein content estimates of winter wheat with a high precision and R-2 and RMSE values of 0.698 and 0.726 ***(-1), and 0.758% and 1.16%, respectively. This study provides a more robust method for estimating the grain yield and protein content of winter wheat based on the integration of the DSSAT-CERES crop model and remote sensing data.

关键词： Hyperspectral DSSAT-CERES winter wheat particle swarm optimization algorithm yield grain protein content

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Multi_objective Model of Mixed Continuous/Batch Plants Planning Problem and Its particle swarm optimization algorithm

Multi_objective Model of Mixed Continuous/Batch Plants Plann...

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21st Chinese Control and Decision Conference

作者： Xu Xinli Dai Xinhua Hao Ping Wang Wanliang Zhejiang Univ Technol Coll Informat Engn Hangzhou 310014 Zhejiang Peoples R China Zhejiang Univ Technol Software Coll Hangzhou 310014 Zhejiang Peoples R China

ISBN: (纸本)9781424427239

A multi-objective, multi-level, multi-product, multi-constraint batch planning problem is abstracted from production of diaphragm caustic soda, and the problem is formulated as a mathematic optimization model with constraints involved resources, work manufacture processes and production capacity etc. Some sub_objectives were considered in the problem model, such as total profit amount, profit margin, total energy wastage and wastage per ten thousand RMB.A modified particle swarm optimization algorithm with a percent-coding and dynamic-bounds coding scheme is proposed for the problem. The validity and flexibility of the model and algorithm are verified by calculating the data from production practices numerically.

关键词： Medium-term Planning Problem particle swarm optimization algorithm Multi_objective

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AN IMPROVED NEURAL NETWORK ADAPTIVE SLIDING MODE CONTROL USED IN ROBOT TRAJECTORY TRACKING CONTROL

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INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL 2015年第5期11卷 1655-1666页

作者： Liu, Tianhua Yin, Shoulin Shenyang Normal Univ Software Coll 253 North Huanghe St Shenyang 110034 Liaoning Peoples R China

This paper proposes an improved neural network adaptive sliding mode control method based on the neural network sliding mode control to improve the performance of the robot trajectory tracking control. This new scheme regards neural network as a controller and adopts robust control law to eliminate the approximation error which uses its nonlinear mapping ability to approximate various unknown nonlinear systems. Hidden layer units and network structure parameter have an effect on neural network mapping. So we will decrease chattering. We conduct experiments with three joints robot and give an example to verify this paper's scheme under the MATLAB platform. The results of experiments show that the new neural network adaptive sliding mode control has a good control accuracy and robustness than other control methods. The new scheme reduces the chattering effectively and also decreases the effect of hidden layer units and network structure parameter on neural network mapping. It will be a good choice for the robot trajectory tracking control.

关键词： Robot tracking Neural network Neural network adaptive sliding mode control particle swarm optimization algorithm Chattering

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Robust H-infinity Tracking Control Combined with Optimized PSS by PSO algorithm for Multimachine Power System

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JOURNAL OF ELECTRICAL SYSTEMS 2015年第1期11卷 36-48页

作者： Dib, Faiza Ben Meziane, Khaddouj Boumhidi, Ismail Sidi Mohamed Ben Abdellah Univ Fac Sci Dept Phys LESSI Lab Dhar Elmahrez Fez Morocco

In this paper, the proposed controller design is based on H-infinity tracking control combined with the optimized Power System Stabilizer (PSS). In addition the parameters of the PSS controller are optimized using the particle swarm optimization algorithm (PSO). The aim of this study is to obtain a high performance for the speed deviation and the angle rotor simultaneously, also the damping of the oscillations and the enhancing power system stability. Using the H-infinity tracking control show the convergence of the errors to the neighborhood of zero. In order to test the effectiveness of the proposed method, the simulation results clearly indicate the damping of the oscillations of the angle rotor and angular speed with reduced overshoots which confirms the performance of the proposed scheme.

关键词： H-infinity tracking control power system stabilizer particle swarm optimization algorithm multi machine power system

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ANFIS Based Time Series Prediction Method of Bank Cash Flow Optimized by Adaptive Population Activity PSO algorithm

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INFORMATION 2015年第3期6卷 300-313页

作者： Wang, Jie-Sheng Ning, Chen-Xu Univ Sci & Technol Liaoning Sch Elect & Informat Engn Anshan 114044 Liaoning Peoples R China

In order to improve the accuracy and real-time of all kinds of information in the cash business, and solve the problem which accuracy and stability is not high of the data linkage between cash inventory forecasting and cash management information in the commercial bank, a hybrid learning algorithm is proposed based on adaptive population activity particle swarm optimization (APAPSO) algorithm combined with the least squares method (LMS) to optimize the adaptive network-based fuzzy inference system (ANFIS) model parameters. Through the introduction of metric function of population diversity to ensure the diversity of population and adaptive changes in inertia weight and learning factors, the optimization ability of the particle swarm optimization (PSO) algorithm is improved, which avoids the premature convergence problem of the PSO algorithm. The simulation comparison experiments are carried out with BP-LMS algorithm and standard PSO-LMS by adopting real commercial banks' cash flow data to verify the effectiveness of the proposed time series prediction of bank cash flow based on improved PSO-ANFIS optimization method. Simulation results show that the optimization speed is faster and the prediction accuracy is higher.

关键词： time series prediction bank cash flow adaptive network-based fuzzy inference system particle swarm optimization algorithm

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