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Fault Diagnosis of On-Load Tap-Changer Based on Variational Mode Decomposition and Relevance Vector Machine

ENERGIES 2017年第7期10卷 946-946页

作者： Liu, Jinxin Wang, Guan Zhao, Tong Zhang, Li Shandong Univ Sch Elect Engn Jinan 250061 Shandong Peoples R China Shandong Prov Key Lab UHV Transmiss Technol & Equ Jinan 250061 Shandong Peoples R China

In order to improve the intelligent diagnosis level of an on-load tap-changer's (OLTC) mechanical condition, a feature extraction method based on variational mode decomposition (VMD) and weight divergence was proposed. The harmony search (HS) algorithm was used to optimize the parameter selection of the relevance vector machine (RVM). Firstly, the OLTC vibration signal was decomposed into a series of finite-bandwidth intrinsic mode function (IMF) by VMD under different working conditions. The weight divergence was extracted to characterize the complexity of the vibration signal. Then, weight divergence was used as training and test samples of the harmony search optimization-relevance vector machine (HS-RVM). The experimental results suggested that the proposed integrated model has high fault diagnosis accuracy. This model can accurately extract the characteristics of the mechanical condition, and provide a reference for the practical OLTC intelligent fault diagnosis.

关键词： on-load tap-changer variational mode decomposition relevance vector machine harmony search algorithm mechanical condition

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MUSIC-MAS: Modeling a harmonic composition system with virtual organizations to assist novice composers

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EXPERT SYSTEMS WITH APPLICATIONS 2016年 57卷 345-355页

作者： Navarro, Maria Manuel Corchado, Juan Demazeau, Yves Univ Salamanca C Espejo S-N Salamanca 37007 Spain Lab Informat Grenoble 110 Ave ChimDomaine Univ St Martin dHres F-38041 Grenoble France

Many music students today experience difficulties in composing melodies without a prior harmonical guide. While harmony can be helpful in creating a melody the generation of harmony is challenging due to the many factors that must be taken into account, such as style, harmonic functions, musical consonance or aesthetics. Although various solutions have been proposed in the past, our study employs a different expert solution based on virtual organizations to make musical harmonies, which can assist novice improvisers and/or composers. The virtual organizations are implemented with Multi-Agent System (MAS) using PANGEA (Platform for Automatic coNstruction of orGanizations of intElligent Agents), a platform to develop different multiagent systems. The main goal is to simulate an expert multiagent system that can compose harmony following specific rules. To do so, the harmony search algorithm is implemented as the main behavior of the composer agent, and adapted to a Belief-Desire-Intention architecture. The application of a VO has not been previously used in the development of this kind of expert system in music. We measured the quality of the music obtained, by minimizing a mathematical function. Additionally, we developed an evaluation test that positively validates the musical results from the perspective of consonance and usefulness of the composers. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： harmony Consonance Tension Multi-agent system Virtual organization harmony search algorithm

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Design and analysis of a novel UWB bandpass filter using 3-D EM simulation-based neural network model with HSA

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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2016年第2期24卷 656-668页

作者： Demirel, Salih Uyanik, Cafer Yildiz Tech Univ Dept Elect & Commun Engn Istanbul Turkey

This paper presents a new systematic analysis and design of the ultrawide-band bandpass filter by using the 3-D electromagnetic simulation-based multilayer perceptron neural network (MLP NN) model of unit elements. This MLP NN model is utilized efficiently as a fast and accurate model within a harmony search algorithm (HSA) procedure to determine the resultant optimum microstrip structure geometry. Moreover, the validity and efficiency of the HSA is manifested by comparing it with those of the standard metaheuristics, which are genetic and particle swarm algorithms. The filter that shows the best performance is designed and realized. Measurements taken from the realized filter demonstrate the success of this approximation over the band range of 3.1 GHz to 10.6 GHz, with a flat group delay performance within that range.

关键词： harmony search algorithm ultrawide-band bandpass filter multilayer perceptron neural network

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Integrating metaheuristics and Artificial Neural Networks for improved stock price prediction

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EXPERT SYSTEMS WITH APPLICATIONS 2016年 44卷 320-331页

作者： Gocken, Mustafa Ozcalici, Mehmet Boru, Asli Dosdogru, Ayse Tugba Adana Sci & Technol Univ Dept Ind Engn TR-01180 Adana Turkey Kilis 7 Aralik Univ Business & Adm Dept Kilis Turkey Gaziantep Univ Dept Ind Engn Gaziantep Turkey

Stock market price is one of the most important indicators of a country's economic growth. That's why determining the exact movements of stock market price is considerably regarded. However, complex and uncertain behaviors of stock market make exact determination impossible and hence strong forecasting models are deeply desirable for investors' financial decision making process. This study aims at evaluating the effectiveness of using technical indicators, such as simple moving average of close price, momentum close price, etc. in Turkish stock market. To capture the relationship between the technical indicators and the stock market for the period under investigation, hybrid Artificial Neural Network (ANN) models, which consist in exploiting capabilities of harmony search (HS) and Genetic algorithm (GA), are used for selecting the most relevant technical indicators. In addition, this study simultaneously searches the most appropriate number of hidden neurons in hidden layer and in this respect;proposed models mitigate well-known problem of overfitting/underfitting of ANN. The comparison for each proposed model is done in four viewpoints: loss functions, return from investment analysis, buy and hold analysis, and graphical analysis. According to the statistical and financial performance of these models, HS based ANN model is found as a dominant model for stock market forecasting. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Artificial Neural Network Genetic algorithm harmony search algorithm Stock market price

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Application of improved support vector regression model for prediction of deformation modulus of a rock mass

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ENGINEERING WITH COMPUTERS 2016年第4期32卷 567-580页

作者： Fattahi, Hadi Arak Univ Technol Dept Min Engn Arak Iran

Deformation modulus of a rock mass is one of the crucial parameters used in the design of surface and underground rock engineering structures. Determination of this parameter by testing cylindrical core samples is almost impossible due to the presence of discontinuities. Due to the problems in determining the deformability of jointed rock masses at the laboratory-scale, various in situ test methods such as plate loading tests, dilatometer etc. have been developed. Although these methods are currently the best techniques, they are expensive and time-consuming, and present operational problems. To overcome this difficulty, in this paper, presents the results of the application of hybrid support vector regression (SVR) with harmony search algorithm , differential evolution algorithm and particle swarm optimization algorithm (PSO). The optimized models were applied to available data given in open source literature and the performance of optimization algorithm was assessed by virtue of statistical criteria. In these models, rock mass rating (RMR), depth, uniaxial compressive strength of intact rock (UCS) and elastic modulus of intact rock (E (i)) were utilized as the input parameters, while the deformation modulus of a rock mass was the output parameter. The comparative results revealed that hybrid of PSO and SVR yield robust model which outperform other models in term of higher squared correlation coefficient (R (2)) and variance account for (VAF) and lower mean square error (MSE), root mean squared error (RMSE) and mean absolute percentage error (MAPE).

关键词： Deformation modulus Support vector regression harmony search algorithm Differential evolution algorithm Particle swarm optimization algorithm

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A comparative study on optimum design of multi-element truss structures

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STEEL AND COMPOSITE STRUCTURES 2016年第3期22卷 521-535页

作者： Artar, Musa Bayburt Univ Dept Civil Engn TR-69000 Bayburt Turkey

A harmony search (HS) and Genetic algorithms (GA), two powerful metaheuristic search techniques, are used for minimum weight designs of different truss structures by selecting suitable profile sections from a specified list taken from American Institute of Steel Construction (AISC). A computer program is coded in MATLAB interacting with SAP2000-OAPI to obtain solution of design problems. The stress constraints according to AISC-ASD (Allowable Stress Design) and displacement constraints are considered for optimum designs. Three different truss structures such as bridge, dome and tower structures taken from literature are designed and the results are compared with the ones available in literature. The results obtained from the solutions for truss structures show that optimum designs by these techniques are very similar to the literature results and HS method usually provides more economical solutions in multi-element truss problems.

关键词： AISC-ASD harmony search algorithm genetic algorithm optimum design truss structures

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Hybrid HSA and PSO algorithm for energy efficient cluster head selection in wireless sensor networks

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SWARM AND EVOLUTIONARY COMPUTATION 2016年 30卷 1-10页

作者： Shankar, T. Shanmugavel, S. Rajesh, A. VIT Univ Sch Elect Engn Vellore Tamil Nadu India Natl Engn Coll Kovilpatti Tamil Nadu India

Energy efficiency is a major concern in wireless sensor networks as the sensor nodes are battery-operated devices. For energy efficient data transmission, clustering based techniques are implemented through data aggregation so as to balance the energy consumption among the sensor nodes of the network. The existing clustering techniques make use of distinct Low-Energy Adaptive Clustering Hierarchy (LEACH), harmony search algorithm (HSA) and Particle Swarm Optimization (PSO) algorithms. However, individually, these algorithms have exploration-exploitation tradeoff (PSO) and local search (HSA) constraint. In order to obtain a global search with faster convergence, a hybrid of HSA and PSO algorithm is proposed for energy efficient cluster head selection. The proposed algorithm exhibits high search efficiency of HSA and dynamic capability of PSO that improves the lifetime of sensor nodes. The performance of the hybrid algorithm is evaluated using the number of alive nodes, number of dead nodes, throughput and residual energy. The proposed hybrid HSA-PSO algorithm shows an improvement in residual energy and throughput by 83.89% and 29.00%, respectively, than the PSO algorithm. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Particle Swarm Optimization harmony search algorithm LEACH Wireless sensor network

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An improved meta-heuristic approach for solving identical parallel processor scheduling problem

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE 2016年第6期230卷 1114-1126页

作者： Bathrinath, S. Saravanasankar, S. Mahapatra, S. S. Singh, Manas Ranjan Ponnambalam, S. G. Kalasalingam Univ Dept Mech Engn Krishnankoil India Natl Inst Technol Rourkela Dept Mech Engn Rourkela 769008 India Monash Univ Malaysia Sch Engn Bandar Sunway Malaysia

This article considers the problem of scheduling n jobs on m identical parallel processors where an optimal schedule is defined as one that produces minimum makespan (the completion time of the last job) and total tardiness among the set of schedules. Such a problem is known as identical parallel processor makespan and total tardiness problem. In order to minimize makespan and total tardiness of identical parallel processors, improved versions of particle swarm optimization and harmony search algorithm are proposed to enhance scheduling performance with less computational burden. The major drawback of particle swarm optimization in terms of premature convergence at initial stage of iterations is avoided through the use of mutation, a commonly used operator in genetic algorithm, by introducing diversity in the solution. The proposed algorithm is termed as particle swarm optimization with mutation. The convergence rate of harmony search algorithm is improved by fine tuning of parameters such as pitch adjusting rate and bandwidth for improving the solution. The performance of the schedules is evaluated in terms of makespan and total tardiness. The results are analyzed in terms of percentage deviation of the solution from the lower bound on makespan. The results indicate that particle swarm optimization with mutation produces better solutions when compared with genetic algorithm and particle swarm optimization in terms of average percentage deviation. However, harmony search algorithm outperforms genetic algorithm, particle swarm optimization, and particle swarm optimization with mutation in terms of average percentage deviation. In certain instances, the solution obtained by harmony search algorithm outperforms existing clonal selection particle swarm optimization.

关键词： Identical parallel processors genetic algorithm particle swarm optimization mutation harmony search algorithm makespan total tardiness

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Predicting anomalous zone ahead of tunnel face utilizing electrical resistivity: I. algorithm and measuring system development

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TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY 2016年第Nov.期60卷 141-150页

作者： Park, Jinho Lee, Kang-Hyun Park, Jeongjun Choi, Hangseok Lee, In-Mo Korea Univ Sch Civil Environm & Architectural Engn Seoul South Korea Korea Expressway Corp Res Inst Disaster & Safety Res Div Gimcheon Si Gyeongsangbuk D South Korea

This study applies the harmony search (HS) inverse analysis algorithm and develops the tunnel resistivity prediction (TRP) system for predicting the location, thickness, permittivity ratio, and conductivity of the anomalous zone ahead of the tunnel face by utilizing electrical resistivity. The relationship between the four characteristic values of the anomalous zone and the electrical resistance is derived using Gauss' laws and Ohm's laws. The optimum values of HS algorithm operators (such as the harmony memory considering rate (HMCR) and the pitch adjust rate (PAR)) are proposed that can provide the best inverse analysis that correlates the four characteristic values with the electrical resistance. Also, the prediction accuracy of inverse analysis using the proposed HS algorithm is verified by laboratory tests on the artificially formed ground with an anomaly. An electrical resistance measuring system is devised to obtain the electrical resistance of the ground, and inverse analyses are performed from the measured resistance to estimate the four characteristic values of the artificial anomaly. The test results from laboratory scale experiments show that the characteristics of the anomalies are predicted reasonably well, resulting in less than 3% average error. This paper is part 1 of the companion papers;the second paper will verify the developed system through the field tests. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Tunnel resistivity prediction harmony search algorithm Anomalous zone Resistivity survey Ahead tunnel face

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Risk-constrained multi-level framework for coordination of generation and transmission expansion planning in liberalised environments - part II: method and case studies

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IET GENERATION TRANSMISSION & DISTRIBUTION 2016年第13期10卷 3191-3200页

作者： Shivaie, Mojtaba Ameli, Mohammad T. Shahid Beheshti Univ Dept Elect Engn AC Tehran Iran

This paper presents a new hybrid method for solving the proposed multi-level optimisation problem, as described in Part I. The hybrid method employs a novel two-stage multi-dimensional melody search algorithm (MSA) with an innovative alternative improvisation procedure (AIP). This hybrid method handles the different levels of the proposed multi-level framework. The two-stage multi-dimensional MSA is a recently developed optimisation algorithm, which is derived from the harmony search algorithm (HSA). Unlike the HSA, the MSA uses different player memories and a group improvisation procedure for finding the best substitution of pitches within a melody. These two features can enhance the performance of the MSA in comparison with the HSA. In addition, to improve the efficiency of the proposed MSA, an innovative improvisation scheme based on the AIP is used for generating new melodies. The proposed methodology has been applied on the 46-bus south Brazilian electric power grid and the IEEE 118-bus test system under two different scenarios in order to demonstrate the feasibility and capabilities of the newly developed framework. The obtained results from case studies validate sufficiency and profitableness of the offered multi-level framework.

关键词： power generation planning power transmission planning risk management optimisation power grids search problems risk-constrained multilevel framework generation expansion planning coordination transmission expansion planning coordination multilevel optimisation problem novel two-stage multidimensional melody search algorithm two-stage multidimensional MSA alternative improvisation procedure AIP optimisation algorithm harmony search algorithm HSA player memories group improvisation procedure 46-bus south Brazilian electric power grid IEEE 118-bus test system

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