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gravitational search algorithm based solution for a class of ternary diophantine equations

JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2016年第4期16卷 899-911页

作者： Balachandar, S. Raja Kannan, K. Srikanth, R. Balachandran, S. Venkatesh, S. G. Balasubramanian, K. Sastra Univ Sch Humanities & Sci Dept Math Thanjavur India

This paper introduces gravitational search algorithm (GSA) to find numerical solutions of Diophantine equations, for which there exists no general method of finding solutions. This algorithm finds upon introducing randomization concept along with the two of the four primary parameters 'velocity' and 'gravity' in physics. The performance of this algorithm has been evaluated on a set of random values. Computed result shows that the gravitational search algorithm - based heuristic is capable of producing high quality solutions, can offer many solutions of such equations.

关键词： gravitational search algorithm gravity Newton's law diophantine equation genetic algorithm particle swarm optimization

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gravitational search algorithm-optimized neural misuse detector with selected features by fuzzy grids-based association rules mining

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NEURAL COMPUTING & APPLICATIONS 2013年第7-8期23卷 2451-2463页

作者： Sheikhan, Mansour Rad, Maryam Sharifi Islamic Azad Univ South Tehran Branch Fac Engn Dept Elect Engn Tehran Iran Islamic Azad Univ South Tehran Branch Dept Comp Engn Tehran Iran

Feature selection is one of the most important techniques for data preprocessing in classification problems. In this paper, fuzzy grids-based association rules mining, as an effective data mining technique, is used for feature selection in misuse detection application in computer networks. The main idea of this algorithm is to find the relationships between items in large datasets so that it detects correlations between inputs of the system and then eliminates the redundant inputs. To classify the attacks, a fuzzy ARTMAP neural network is employed whose training parameters are optimized by gravitational search algorithm. The performance of the proposed system is compared with some other machine learning methods in the same application. Experimental results show that the proposed system, when choosing optimum "feature subset size-adjustment" parameter, performs better in terms of detection rate, false alarm rate, and cost per example in classification problems. In addition, employing the reduced-size feature set results in more than 8.4 percent reduction in computational complexity.

关键词： Misuse detection Neural network gravitational search algorithm Feature selection Data mining Fuzzy clustering Fuzzy association rules

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gravitational search algorithm based data scheduling for peer to peer video on demand system

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MULTIMEDIA TOOLS AND APPLICATIONS 2019年第19期78卷 27291-27307页

作者： AjithaGladis, K. P. CSI Inst Technol Dept IT Thovalai India

In peer to peer (P2P) video streaming systems, peers in network assist to forward the data to other peers without the interference of central servers. Video on Demand (VoD) is widely using internet service, which offers video to users with effective control when they need it. The major significant problem in developing a P2P VoD system is data scheduling, which concentrates on dealing with transmitting and dispatching data segments within a system efficiently. So a gravitational search algorithm based data Scheduling (GSAS) is presented in this paper. Initially, the network is developed in the form of hierarchical topology. Video file is cached as data segments in each peer in the top layer of the network. Using the priority function, these data segments are sorted or prioritized. Using the proposed GSA algorithm, optimal or suitable peers which cache the requested data segments in the top layer are selected. Then the prioritized data segments from the selected peers are scheduled to the peer which has requested for video sequences. The video file "Grandmother" with the size 53 MB is examined in this approach. This proposed approach is simulated in the network simulator. Simulation results show that the performance of this proposed approach is superior to that of the existing work in terms of throughput and scheduling time.

关键词： Peer to peer video streaming systems Video on demand (VoD) gravitational search algorithm Data scheduling Priority function

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gravitational search algorithm-based optimization of hybrid wind and solar renewable energy system

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COMPUTATIONAL INTELLIGENCE 2022年第3期38卷 1106-1132页

作者： Geleta, Diriba Kajela Manshahia, Mukhdeep Singh Punjabi Univ Dept Math Patiala Punjab India Madda Walabu Univ Dept Math Addis Ababa Ethiopia

Due to the issue of environmental protection coupled with high energy demand, there was an initiation for exploration of different renewable energy sources. This article aims to optimize the total annual cost of hybrids of wind and solar renewable energy system to satisfy the predesigned load. Minimization of the total annual cost of the system by determining appropriate numbers of the components, so that the desired load can be economically and reliably satisfied under the given constraints. gravitational search algorithm (GSA) was employed for the optimization process. GSA is a recently proposed metaheuristic algorithm which is based on Newton's universal gravitational law of gravity and mass interactions. It uses stochastic rules to escape local optima and find the global optimal solutions. MATLAB codes were designed for the developed fitness function and employed algorithm. The proposed methodology was run for the fitness function through the code and the results were discussed. The result was compared with the results of Particle Swarm Optimization (PSO) and also shown that: GSA has some advantage over PSO algorithm. Even though, the algorithm has several parameters to be adjusted, it is strong in both local and global optimal searches.

关键词： gravitational search algorithm hybrid renewable energy nature inspired algorithm optimization

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gravitational search algorithm based strategy for combinatorial t-way test suite generation

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JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES 2022年第8期34卷 4860-4873页

作者： Htay, Khin Maung Othman, Rozmie Razif Amir, Amiza Alkanaani, Jalal Mohammed Hachim Univ Malaysia Perlis Fac Elect Engn Technol Arau 02600 Perlis Malaysia Univ Malaysia Perlis Adv Commun Engn ACE Ctr Excellence Kangar 01000 Perlis Malaysia Iraq Univ Coll Dept Comp Engn Basra Iraq

Due to different users' requirements, contemporary software has become feature-rich in terms of input functions (i.e., parameters) and selections (i.e., values). Exhaustive testing on sophisticated software systems is impractical as far as testing time and cost are concerned. Various test case design strategies have been proposed in the literature, such as equivalence class partitioning, boundary value analysis and decision tables. Unlike earlier works, combinatorial t-way testing supports the detection of faults caused by two or more input parameter interactions and thus efficiently minimizes the size of the test suite. Over the past few years, metaheuristic algorithms have appeared to be the most common choice for researchers since their effectiveness proves to offer optimal/near-optimal results. However, generating a t-way test suite is an NP-hard problem, and no single t-way strategy can guarantee to show superiority to others for all types of system configurations. Hence, this paper presents a new t-way strategy based on the gravitational search algorithm (GSA), known as the gravitational search Test Generator (GSTG). The primary contribution of this paper is that GSA has adapted for the first time to t-way test data generation. The benchmarking results showcase that GSTG obtains competitive results in most system configurations compared to other existing strategies and addresses higher combination coverage (i.e., t <= 10). (C) 2021 The Authors. Published by Elsevier B.V. on behalf of King Saud University.

关键词： Combinatorial testing T-way test suites Interaction testing Metaheuristic gravitational search algorithm

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gravitational search algorithm for determining controller parameters in an automatic voltage regulator system

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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2016年第4期24卷 2387-2400页

作者： Duman, Serhat Yorukeren, Nuran Altas, Ismail H. Duzce Univ Fac Technol Dept Elect & Elect Engn Duzce Turkey Kocaeli Univ Dept Elect Engn Fac Engn Kocaeli Turkey Karadeniz Tech Univ Fac Engn Dept Elect & Elect Engn Trabzon Turkey

This paper presents optimal tuning of the controller parameters of a proportional-integral-derivate (PID) controller for an automatic voltage regulator (AVR) system using a heuristic gravitational search algorithm (GSA) based on mass interactions and Newton's law of gravity. The determination of optimal controller parameters is considered an optimization problem in which different performance indexes and a performance criterion in the time domain have been used as objective functions to test the performance and effectiveness of the GSA. In the determining process of the parameters, the designed PID controller with the proposed approach is simulated under different conditions and the performance of the controller is compared with those reported in the literature. From the numerical simulation results it is clear that the GSA approach is successfully applied to reveal the performance and the feasibility of the proposed controller in the AVR system.

关键词： gravitational search algorithm optimization automatic voltage regulator

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gravitational search algorithm for Optimal Distributed Generation Operation in Autonomous Network

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2014年第10期39卷 7183-7188页

作者： Jamian, J. J. Mustafa, M. W. Mokhlis, H. Baharudin, M. A. Abdilahi, A. M. Univ Teknol Malaysia Skudai 81310 Malaysia Univ Malaya Kuala Lumpur 50603 Malaysia

The gravitational search algorithm (GSA) has been used in this research to optimize output of the multiple distributed generator (DG) units in autonomous distribution network. With the optimal operation of DGs, the voltage profile can be improved, thus reducing the power losses in the system. The performance of GSA is compared with an established paper, which uses the genetic algorithm (GA) in analysing similar problem. The results show that the GSA has superior performance in finding the optimal DG output compared to the GA technique, either in terms of power loss as well as the voltage profile. Furthermore, the consistency of the proposed GSA method is proven by the small standard deviation value obtained from 20 repetitions of the same analysis.

关键词： Autonomous network Distributed generation gravitational search algorithm Power loss minimization Standard deviation

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gravitational search algorithm based optimization technique for enhancing the performance of self excited induction generator

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INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2019年第5期10卷 1082-1090页

作者： Paliwal, Swati Sinha, Sanjay Kumar Chauhan, Yogesh Kumar Amity Univ Uttar Pradesh Dept Elect & Elect Engn Noida Uttar Pradesh India Kamla Nehru Inst Technol Dept Elect Engn Sultanpur India

y In wind based micro generation schemes, 3-phase self excited induction generators are prominently used in order to fulfil single phase load requirement. Hence in this context, this paper presents a 3-phase, 5.5 kW, 415 V, 50 Hz short shunt self excited induction generator for improving the voltage regulation and optimum performance of induction machine by using heuristic approach named as gravitational search algorithm. It is used in order to get the optimum capacitance values at specified speed for optimized voltage regulation and performance characteristics in terms of root mean square error and mean absolute error and mean square error. This optimization technique works on Newton law of gravity and it provides average best results for validating the performance in order to enhance machine parameters used in wind energy conversion system.

关键词： SEIG gravitational search algorithm Optimization gravitational law Loadability

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gravitational search algorithm–based fuzzy control for a nonlinear ball and beam system

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Journal of Control and Decision 2018年第3期5卷 229-240页

作者： M.J.Mahmoodabadi N.Danesh Department of Mechanical Engineering Sirjan University of TechnologySirjanIran

In recent decades,fuzzy logic and its application for stabilising nonlinear systems have had a great *** this paper,a novel optimal fuzzy controller is provided to control a ball and beam *** fuzzy control force is calculated via a fuzzy system based on the singleton fuzzifier,the centre average defuzzifier and the product inference *** further improve the control performance,the gravitational search algorithm is applied to optimise the controller *** obtained simulation results indicate that the proposed scheme can provide a better performance in the case of convergence rate and accuracy in comparison with those of other recently published works.

关键词： Fuzzy controller gravitational search algorithm optimal control nonlinear system ball and beam system

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gravitational search algorithm Based Design of Optimal Wideband IIR Digital Differentiator 12

Gravitational Search Algorithm Based Design of Optimal Wideb...

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12 IEEE Int C Elect Energy Env Communications Computer Control

作者： Kumar, Manjeet Rawat, Tarun Kumar Jain, Aman Netaji Subhas Inst Technol Div Elect & Commun Engn Delhi 110078 India

ISBN: (纸本)9781467365406

This paper aims to design IIR digital differentiator by adopting a new heuristic algorithm called a gravitational search algorithm (GSA). In GSA, agents are treated as the masses and the force of attraction between agents is calculated based on Newton's gravitation law to find optimal solutions to the problem. The agent with greater mass is treated as the near optimal solution and their position is a reflection of the solution. Simulations to find optimal filter coefficients of second, third and fourth order differentiators using GSA have been performed. Total absolute magnitude error and maximum phase error are the performance measures that are used to evaluate performance of the proposed differentiators. The result of the proposed GSA based approach has been compared with the standard existing algorithms like PSO, GA, SA, pole zero (PZ) and segment rule. Simulations show that GSA gives superior results when compared with the optimization abilities of other standard algorithms.

关键词： Digital Differentiator Infinite Impulse Response Heuristic algorithm gravitational search algorithm

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