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International Conference on Inventive Computation Technologies

作者： Ananthi Sheshasaayee D. SRIDEVI Quaid-e-millath Govt. College for Women (autonomous) Chennai Tamil Nadu India Computer Science Department Research Scholar Sri Chandrasekharendra Saraswathi Viswa Maha Vidyalaya Kanchipuram Tamil Nadu India

ISBN: (纸本)9781509012862

There has been unprecedented growth of spatial data encountered in different application domains and their analysis has become more important and practically relevant. Clustering is one of the important tasks in spatial data mining and its issues have been extensively studied. In this paper, we propose a new hybrid approach for data clustering. Initially the proposed approach exploits spatial fuzzy c-means for clustering the vertex into homogeneous regions. In order to improve the performance of fuzzy c-means to cope with segmentation problems, we employ gravitational search algorithm which is inspired by Newton's rule of gravity. gravitational search algorithm is incorporated into fuzzy c-means to take advantage of its ability to find optimum cluster centers which minimizes the fitness function of fuzzy c-means.

关键词： Spatial Data Mining gravitational search algorithm Fuzzy c- means Regionalization

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Disruption based gravitational search algorithm for short term hydrothermal scheduling

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EXPERT SYSTEMS WITH APPLICATIONS 2015年第20期42卷 7000-7011页

作者： Gouthamkumar, N. Sharma, Veena Naresh, R. Natl Inst Technol Hamiipur Dept Elect Engn Hamiipur 177005 Himachal Prades India

This paper proposes a disruption based gravitational search algorithm (DGSA) to find the optimum solution for short term hydrothermal scheduling (STHTS) problem, which considers the cascading nature of hydro plants, water transportation time delays between reservoirs, variable hourly water discharge limits, reservoir storage volume limits, hydraulic continuity constraint, initial and final reservoir storage volume limits, power system load balance, generation limits of hydro and thermal units and valve point loading effects of thermal plants. In the proposed approach, a disruption operator based on astrophysics has been integrated into gravitational search algorithm (GSA) to enhance its performance. It is found that the disruption operator increases both of the exploration and exploitation abilities in comparison with the conventional GSA. Moreover, an effective strategy is utilized to handle the end storage volume constraints and system load balance constraints. Finally, the proposed approach is evaluated on two hydrothermal test systems, one consisting of four hydro plants and an equivalent thermal plant and another with four hydro and three thermal plants. The comparative result analysis shows that the DGSA approach has better solution results and convergence accuracy than the GSA and other approaches reported in literature for solving STHTS problem. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Short term hydrothermal scheduling Cascaded reservoirs gravitational search algorithm Disruption based gravitational search algorithm

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Short-term economic environmental hydrothermal scheduling using improved multi-objective gravitational search algorithm

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ENERGY CONVERSION AND MANAGEMENT 2015年 89卷 127-136页

作者： Li, Chunlong Zhou, Jianzhong Lu, Peng Wang, Chao Huazhong Univ Sci & Technol Sch Hydropower & Informat Engn Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Hubei Key Lab Digital Valley Sci & Technol Wuhan 430074 Peoples R China

With growing concerns about energy and environment, short-term economic environmental hydrothermal scheduling (SEEHS) plays a more and more important role in power system. Because of the two objectives and various constraints, SEEHS is a complex multi-objective optimization problem (MOOP). In order to solve the problem, we propose an improved multi-objective gravitational search algorithm (IMOGSA) in this paper. In IMOGSA, the mass of the agent is redefined by multiple objectives to make it suitable for MOOP. An elite archive set is proposed to keep Pareto optimal solutions and guide evolutionary process. For balancing exploration and exploitation, a neighborhood searching mechanism is presented to cooperate with chaotic mutation. Moreover, a novel method based on feasible space is proposed to handle hydro plant constraints during SEEHS, and a violation adjustment method is adopted to handle power balance constraint. For verifying its effectiveness, the proposed IMOGSA is applied to a hydrothermal system in two different case studies. The simulation results show that IMOGSA has a competitive performance in SEEHS when compared with other established algorithms. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Economic environmental hydrothermal scheduling Multi-objective optimization gravitational search algorithm Elite archive set Neighborhood searching mechanism Constraint handling method

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A modified gravitational search algorithm based on sequential quadratic programming and chaotic map for ELD optimization

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KNOWLEDGE AND INFORMATION SYSTEMS 2015年第3期42卷 689-708页

作者： Han, XiaoHong Quan, Long Xiong, Xiaoyan Taiyuan Univ Technol Minist Educ China Key Lab Adv Transducers & Intelligent Control Sys Taiyuan 030024 Peoples R China

gravitational search algorithm (GSA) is a stochastic search algorithm based on the law of gravity and mass interactions. For the purpose of enhancing the performance of standard GSA, this paper proposes a robust hybrid gravitational search algorithm (RHGSA). This algorithm makes the best of ergodicity of PieceWise Linear chaotic map to explore the global search while utilizing the sequential quadratic programming to accelerate the local search. To verify the performance of RHGSA, different types of benchmark functions including five unimodal functions and ten functions provided by CEC 2005 special session are tested in the experiments. Comparisons with other new variants of POS and GSA show that RHGSA obtains a promising performance on the majority of the test problems. Furthermore, a practical application problem, the economic load dispatch problem of power systems (ELD), is solved to further evaluate RHGSA. Compared with the previous evolutionary algorithms applied to ELD problem, RHGSA can get better results.

关键词： Function optimization Heuristic search algorithm Swarm intelligence gravitational search algorithm Sequential quadratic programming PieceWise Linear chaotic map

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A Clustering Based Archive Multi Objective gravitational search algorithm

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FUNDAMENTA INFORMATICAE 2015年第4期138卷 387-409页

作者： Abbasian, Mohammad Amir Nezamabadi-pour, Hossein Amoozegar, Maryam Shahid Bahonar Univ Kerman Dept Elect Engn Kerman Iran Grad Univ Adv Technol Inst Sci & High Technol & Environm Sci Dept Informat Technol Kerman Iran

gravitational search algorithm(GSA) is a recent createdmetaheuristic optimization algorithm with good results in function optimization as well as real world optimization problems. Many real world problems involve multiple (often conflicting) objectives, which should be optimized simultaneously. Therefore, the aim of this paper is to propose a multi-objective version of GSA, namely clustering based archive multi-objective GSA (CA-MOGSA). Proposed method is created based on the Pareto principles. Selected non-dominated solutions are stored in an external archive. To control the size of archive, the solutions with less crowding distance are removed. These strategies guarantee the elitism and diversity as two important features of multi-objective algorithms. The archive is clustered and a cluster is randomly selected for each agent to apply the gravitational force to attract it. The selection of the proper cluster is based on the distance between clusters representatives and population member (the agent). Therefore, suitable trade-off between exploration and exploitation is provided. The experimental results on eight standard benchmark functions reveal that CA-MOGSA is a well-organized multi-objective version of GSA. It is comparable with the state-of-the-art algorithms including non-dominated sorting genetic algorithm-II (NSGA-II), strength Pareto evolutionary algorithm (SPEA2) and better than multi-objective GSA (MOGSA), time-variant particle swarm optimization (TV-PSO), and non-dominated sorting GSA (NSGSA).

关键词： Multi objective optimization gravitational search algorithm Archive clustering diversity preservation elitism

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A new design method for adaptive IIR system identification using hybrid particle swarm optimization and gravitational search algorithm

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NONLINEAR DYNAMICS 2015年第4期79卷 2553-2576页

作者： Jiang, Shanhe Wang, Yan Ji, Zhicheng Jiangnan Univ Inst Elect Automat Key Lab Adv Proc Control Light Ind Minist Educ Wuxi 214122 Peoples R China Anqing Normal Coll Dept Phys & Power Engn Anqing 246011 Peoples R China

Design of adaptive infinite impulse response (IIR) filter is the process of utilizing adaptive algorithm to iteratively determine the filter parameters to obtain an optimal model for the unknown plant based on minimizing the error cost function. However, the error cost surface of IIR filter is generally nonlinear, non-differentiable and multimodal. Hence, an efficient global optimization technique is required to minimize the error cost objective. A novel hybrid particle swarm optimization and gravitational search algorithm (HPSO-GSA) is proposed in this paper for IIR filter design. The proposed HPSO-GSA updates particle positions through obeying the influence of gravity acceleration in GSA and receiving direction of cognitive memory and social sharing information from PSO by means of coevolutionary strategy. The effect of key parameters on the performance of the proposed algorithm is firstly studied, and the proper parameters in HPSO-GSA are established using five benchmark plants along with the same-order model. The simulation studies have been performed for the performance comparison of eight algorithms such as PSO, GSA, QPSO, DPSO, FO-DPSO, GAPSO, PSOGSA and the proposed HPSO-GSA for unknown IIR system identification with the same-order and reduced-order filters. Simulation results show that the proposed algorithm has advantages over PSO, GSA and other PSO-based variants in terms of the convergence speed and the MSE levels.

关键词： IIR system identification Particle swarm optimization gravitational search algorithm Hybrid approach

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Fuzzy logic in the gravitational search algorithm enhanced using fuzzy logic with dynamic alpha parameter value adaptation for the optimization of modular neural networks in echocardiogram recognition

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APPLIED SOFT COMPUTING 2015年 37卷 245-254页

作者： Gonzalez, Beatriz Valdez, Fevrier Melina, Patricia Prado-Arechiga, German Tijuana Inst Technol Tijuana Mexico

In this paper the main goal is to find the optimal architecture of modular neural networks, which means finding out the optimal number of modules, layers and nodes of the neural network. The fuzzy gravitational search algorithm with dynamic parameter adaptation is used for optimizing the modular neural network in a particular pattern recognition application. The proposed method is applied to medical images in echocardiogram recognition. One of the most common methods for detection and analysis of diseases in the human body, by physicians and specialists, is the use of medical images. Simulation results of the proposed approach in echocardiogram recognition show the advantages of using the fuzzy gravitational search in the optimization of modular neural networks. In this case the proposed approach provides a very good 99.49% echocardiogram recognition rate. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Modular neural network gravitational search algorithm Pattern recognition Echocardiograms GSA Fuzzy logic

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Optimal StatCom Placement using gravitational search algorithm

Optimal StatCom Placement using Gravitational Search Algorit...

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International Conference on Power Electronics, Intelligent Control and Energy Systems

作者： Bharat Singh Rana Laxmi Srivastava Electrical Engineering Department Madhav Institute of Technology & Science Gwalior India

ISBN: (纸本)9781467385886

A nature inspired evolutionary computing approach called, gravitational search algorithm (GSA) has been proposed for optimal placement of StatCom, to maximize the voltage stability margin and also improve voltage profile by minimizing the total voltage deviation in the power system. The proposed nature inspired evolutionary computing approach has been performed using two steps. As the first step, the weakest buses selected for placement of StatCom using modal analysis. In the second step GSA is applied, to select the optimal allocation of StatCom considering these selected weakest buses. Fuzzy performance Index has been used, for combining the various objectives which are conflicting in nature. The proposed nature inspired computing technique (GSA) has been tested on the standard IEEE 14-bus system considering the stressed condition as well as contingencies during stressed condition. To establish the superiority of proposed GSA approach, the results using Genetic algorithm (GA) were compared the performance of GSA. On the basis of comparison, GSA has been found to be superior to GA with respect to it convergence characteristic and accuracy as well.

关键词： Fuzzy Logic gravitational search algorithm Genetic algorithm StatCom Voltage Stability Margin

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Design of multiplier-less sharp transition width non-uniform filter banks using gravitational search algorithm

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INTERNATIONAL JOURNAL OF ELECTRONICS 2015年第1期102卷 48-70页

作者： Bindiya, T. S. Elias, Elizabeth Natl Inst Technol Dept Elect & Commun Engn Calicut Kerala India

In this paper, multiplier-less near-perfect reconstruction tree-structured filter banks are proposed. Filters with sharp transition width are preferred in filter banks in order to reduce the aliasing between adjacent channels. When sharp transition width filters are designed as conventional finite impulse response filters, the order of the filters will become very high leading to increased complexity. The frequency response masking (FRM) method is known to result in linear-phase sharp transition width filters with low complexity. It is found that the proposed design method, which is based on FRM, gives better results compared to the earlier reported results, in terms of the number of multipliers when sharp transition width filter banks are needed. To further reduce the complexity and power consumption, the tree-structured filter bank is made totally multiplier-less by converting the continuous filter bank coefficients to finite precision coefficients in the signed power of two space. This may lead to performance degradation and calls for the use of a suitable optimisation technique. In this paper, gravitational search algorithm is proposed to be used in the design of the multiplier-less tree-structured uniform as well as non-uniform filter banks. This design method results in uniform and non-uniform filter banks which are simple, alias-free, linear phase and multiplier-less and have sharp transition width.

关键词： canonic signed digit differential evolution tree-structured filter banks artificial bee colony frequency response masking gravitational search algorithm

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Power system stability improvement by static synchronous series compensator-based damping controller employing gravitational search algorithm

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INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING 2015年第2期11卷 143-154页

作者： Mohapatra, Sangram Keshori Panda, Sidhartha Satpathy, Prasant Kumar CV Raman Coll Engn Dept Elect Engn Bhubaneswar 752054 Orissa India Veer Surendra Sai Univ Technol Dept Elect & Elect Engn Burla 768018 Odisha India Coll Engn & Technol Dept Elect Engn Bhubaneswar 751003 Orissa India

Power-system stability improvement by a static synchronous series compensator (SSSC)-based damping controller is thoroughly investigated in this paper. The present study considered both local and remote signals with associated time delays. The design problem of the proposed controller is formulated as an optimisation problem, and gravitational search algorithm (GSA) is employed to search for the optimal controller parameters. The performances of the proposed controllers are evaluated under different disturbances for both single-machine infinite bus power system and multi-machine power system. The performance of the proposed controllers with variations in the signal transmission delays has also been investigated. Simulation results are presented under various operating conditions and disturbances to show the effectiveness and robustness of the proposed approach.

关键词： static synchronous series compensator SSSC controller design time delay power system stability gravitational search algorithm GSA single-machine infinite-bus power system multi-machine power system

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