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International Conference on Modelling, Identification and Control

作者： Farid LACHOURI Abdeldjallil KHELIFI Lyes TIGHZERT Thafsouth AGUERCIF Boubekeur MENDIL Departement de Genie Electrique Faculte de Technologie Universite de Bejaia Laboratoire de Technologie Industrielle et de l'Information (LTII) Faculte de Technologie Universite de Bejaia

ISBN: (纸本)9781509015948

this paper introduces a new compact intelligent algorithm for global optimization problems. The proposed algorithm is inspired from music improvisation. It is a variant of harmony search algorithm. It is called the compact harmony search algorithm (cHSA). It uses a compact representation to store the harmonies in the memory. The proposed intelligent algorithm is compared to the standard version of harmony search algorithm and the results shown that it is very efficient in terms of convergence uality, accuracy, stability and time processing. We give also an application of the algorithm for the realization of self-standing-up of the humanoid robot hydroid.

关键词： Compact representation Optimization harmony search algorithm Hmanoid robot Self-stunding

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Sensor placement optimization in structural health monitoring using distributed monkey algorithm

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SMART STRUCTURES AND SYSTEMS 2015年第1期15卷 191-207页

作者： Yi, Ting-Hua Li, Hong-Nan Zhang, Xu-Dong Dalian Univ Technol Sch Civil Engn Dalian 116023 Peoples R China Dalian Univ Technol State Key Lab Coastal & Offshore Engn Dalian 116023 Peoples R China

Proper placement of sensors plays a key role in construction and implementation of an effective structural health monitoring (SHM) system. This paper proposes a novel methodology called the distributed monkey algorithm (DMA) for the optimum design of SHM system sensor arrays. Different from the existing algorithms, the dual-structure coding method is adopted for the representation of design variables and the single large population is partitioned into subsets and each subpopulation searches the space in different directions separately, leading to quicker convergence and higher searching capability. After the personal areas of all subpopulations have been finished, the initial optimal solutions in every subpopulation are extracted and reordered into a new subpopulation, and the harmony search algorithm (HSA) is incorporated to find the final optimal solution. A computational case of a high-rise building has been implemented to demonstrate the effectiveness of the proposed method. Investigations have clearly suggested that the proposed DMA is simple in concept, few in parameters, easy in implementation, and could generate sensor configurations superior to other conventional algorithms both in terms of generating optimal solutions as well as faster convergence.

关键词： structural health monitoring optimal sensor placement distributed monkey algorithm harmony search algorithm modal assurance criterion

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One-day-ahead hourly forecasting for photovoltaic power generation using an intelligent method with weather-based forecasting models

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IET GENERATION TRANSMISSION & DISTRIBUTION 2015年第14期9卷 1874-1882页

作者： Huang, Chao-Ming Chen, Shin-Ju Yang, Sung-Pei Kuo, Chung-Jen Kun Shan Univ Dept Elect Engn Tainan 71070 Taiwan Kun Shan Univ Dept Comp & Commun Engn Tainan 71070 Taiwan

An intelligent method is proposed in this study to predict one-day-ahead hourly photovoltaic (PV) power generation. The proposed method comprises data classification, training, forecasting and forecasting updating stages. In the first stage, a fuzzy k-means algorithm is used to classify the historical data of daily PV power generation into various weather types. In the second stage, five training models are established, according to the verbal weather forecast of the Taiwan Central Weather Bureau (TCWB), in terms such as the sunny, sunny and cloudy, cloudy, cloudy and rainy and rainy. Each training model is constructed using a radial basis function neural network (RBFNN), for which the parameters of each RBFNN, including the position of the radial basis function (RBF) centres, the width of the RBFs and the weights between the hidden and the output layers, are optimised using a harmony search algorithm (HSA). In the forecasting stage, fuzzy inference is used to select an adequate forecasting model from the trained models. To cope with the possible fluctuation of PV power generation, the forecasts are updated every 3 h, according to the updated weather forecasts of the TCWB. The proposed approach is tested on a practical PV power generation system. The results show that the proposed method provides better forecasting results than the existing methods over 1-year testing data.

关键词： load forecasting photovoltaic power systems fuzzy set theory fuzzy reasoning fuzzy neural nets learning (artificial intelligence) radial basis function networks search problems weather forecasting power engineering computing one-day-ahead hourly forecasting photovoltaic power generation intelligent method weather-based forecasting model PV power generation data classification fuzzy k-means algorithm training model Taiwan Central Weather Bureau TCWB RBFNN radial basis function neural network harmony search algorithm HSA fuzzy inference time 3 h

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Discussion of "Application of excel solver for parameter estimation of the nonlinear Muskingum models" by Reza Barati

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KSCE JOURNAL OF CIVIL ENGINEERING 2015年第1期19卷 340-342页

作者： Hamedi, Farzan Bozorg-Haddad, Omid Orouji, Hosein Univ Tehran Coll Agr & Nat Resources Fac Agr Engn & Technol Dept Irrigat & Reclamat Engn Tehran Iran

An accurate solution method is essential to the calibration of the nonlinear Muskingum model. Most of the earlier researchers have used inaccurate Euler’s solution method which is manipulated to get a better fit for observed Wilson’s data (1974). Euler’s method which is adopted by most previous researchers is not very accurate and results in unsuitable simulation based on the nonlinear Muskingum model as shown in this discussion. This study proposes fourth-order Runge-Kutta method as a suitable and accurate solution method for simulation stage. When more accuracy is needed, the structure of the Muskingum model can be modified to produce more degree of freedom in model calibration procedure. For this purpose, a new five-parameter nonlinear Muskingum model is proposed. The proposed model is easy to formulate and use. The results show that the improvement in the fit of the proposed nonlinear Muskingum model is substantial.

关键词： KSCE Journal Present Discussion Agricultural Engineer harmony search algorithm Shuffle Frog Leaping algorithm

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Discussion of "application of excel solver for parameter estimation of the nonlinear Muskingum models" by Reza Barati

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KSCE JOURNAL OF CIVIL ENGINEERING 2015年第1期19卷 332-336页

作者： Vatankhah, Ali R. Univ Tehran Univ Coll Agr & Nat Resources Irrigat & Reclamat Eng Dept Karaj *** Iran

An accurate solution method is essential to the calibration of the nonlinear Muskingum model. Most of the earlier researchers have used inaccurate Euler's solution method which is manipulated to get a better fit for observed Wilson's data (1974). Euler's method which is adopted by most previous researchers is not very accurate and results in unsuitable simulation based on the nonlinear Muskingum model as shown in this discussion. This study proposes fourth-order Runge-Kutta method as a suitable and accurate solution method for simulation stage. When more accuracy is needed, the structure of the Muskingum model can be modified to produce more degree of freedom in model calibration procedure. For this purpose, a new five-parameter nonlinear Muskingum model is proposed. The proposed model is easy to formulate and use. The results show that the improvement in the fit of the proposed nonlinear Muskingum model is substantial.

关键词： harmony search harmony search algorithm Clonal Selection algorithm Hydrologic Engineer Muskingum Model

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An interval optimization based day-ahead scheduling scheme for renewable energy management in smart distribution systems

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ENERGY CONVERSION AND MANAGEMENT 2015年 106卷 584-596页

作者： Chen, Chun Wang, Feng Zhou, Bin Chan, Ka Wing Cao, Yijia Tan, Yi Hunan Univ Coll Elect & Informat Engn Changsha 410082 Hunan Peoples R China Hong Kong Polytech Univ Dept Elect Engn Hong Kong Hong Kong Peoples R China

The integration of renewable energy generation into distribution systems has a significant influence on network power losses, nodal voltage profile and security level due to the variability and uncertainty of renewable energy generation. This paper proposes a novel interval optimization based day-ahead scheduling model considering renewable energy generation uncertainties for distribution management systems. In this approach, the forecasting errors of wind speed, solar radiation intensity and loads are formulated as interval numbers so as to avoid any need for accurate probability distribution. In this model, the total nodal voltage deviation and network power losses are optimized for the economic operation of distribution systems with improved power quality. Consequently, the order relation of interval numbers is used to transform the proposed interval optimal scheduling model into a deterministic optimization problem which can then be solved using the harmony search algorithm. Simulation results on 33-node and 119-node systems with renewable energy generation showed that considerable improvements on system nodal voltage profile and power losses can be achieved with multiple interval sources of uncertain renewable energy generation and loads. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Day-ahead scheduling scheme Distribution management systems harmony search algorithm Interval optimization Renewable energy generation

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Non-uniform cosine modulated filter banks using meta-heuristic algorithms in CSD space

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JOURNAL OF ADVANCED REsearch 2015年第6期6卷 839-849页

作者： Kalathil, Shaeen Elias, Elizabeth Natl Inst Technol Calicut Dept Elect & Commun Engn Calicut Kerala India

This paper presents an efficient design of non-uniform cosine modulated filter banks (CMFB) using canonic signed digit (CSD) coefficients. CMFB has got an easy and efficient design approach. Non-uniform decomposition can be easily obtained by merging the appropriate filters of a uniform filter bank. Only the prototype filter needs to be designed and optimized. In this paper, the prototype filter is designed using window method, weighted Chebyshev approximation and weighted constrained least square approximation. The coefficients are quantized into CSD, using a look-up-table. The finite precision CSD rounding, deteriorates the filter bank performances. The performances of the filter bank are improved using suitably modified meta-heuristic algorithms. The different meta-heuristic algorithms which are modified and used in this paper are Artificial Bee Colony algorithm, Gravitational search algorithm, harmony search algorithm and Genetic algorithm and they result in filter banks with less implementation complexity, power consumption and area requirements when compared with those of the conventional continuous coefficient non-uniform CMFB. (C) 2014 Production and hosting by Elsevier B.V. on behalf of Cairo University.

关键词： Cosine modulation Non-uniform filter banks Artificial Bee Colony algorithm Gravitational search algorithm harmony search 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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2010 Chinese Control and Decision Conference

作者： Liqun Gao~1,Dexuan Zou~1,Yanfeng Ge~(1,2),Wenjing Jin~1 1.School of Information Science and Engineering,Northeastern University,Shenyang,110004 2.Liaoning Electric Power Company Limited,Shenyang,110004

We use an effective global harmony search algorithm(EGHS)to solve two kinds of pressure vessel design *** general,the two problems are formulated as mixed-integer non-linear programming problems with several *** EGHS combines harmony search algorithm(HS)with concepts from the swarm intelligence of particle swarm optimization algorithm(PSO)to solve the two optimization *** EGHS algorithm has been applied to two typical problems with results better than previously *** 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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A Novel Discrete harmony search algorithm for Scheduling Lot-streaming Flow Shops

A Novel Discrete Harmony Search Algorithm for Scheduling Lot...

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The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

作者： Quan-Ke Pan Jun-hua Duan Junqing Li Kaizhou Gao J. J. Liang College of Computer Science Liaocheng University Liaocheng 252059 PR China School. Electrical Engineering Zhengzhou University

This paper proposes a novel discrete harmony search (DHS) algorithm to minimize makespan for a lot-streaming flow shop scheduling problem with sequence dependent setup times. Unlike the traditional harmony search (HS) algorithm, the proposed DHS algorithm utilizes job permutations to represent harmonies and applies a job-permutation-based improvisation to generate new harmonies. To enhance the algorithm’s searching ability, an effective initialization scheme based on the NEH heuristic is developed to construct an initial harmony memory with certain quality and diversity, and an efficient local search algorithm based on the insert neighborhood structures is fused to stress the local exploitation. Extensive computational simulations and comparisons are provided, which demonstrate the effectiveness of the proposed DHS against the best performing algorithms from the literature.

关键词： Flow shop scheduling Lot-streaming harmony search algorithm Makespan

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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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The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

作者： Dexuan Zou Wenjing Jin Liqun Gao Yanfeng Ge School of Information Science and Engineering Northeastern University Shenyang 110004 School of Information Science and Engineering Northeastern University Shenyang 110004 Liaoning El

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

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