Improved Gravitational Search Algorithm (GSA) Using Fuzzy Logic
Researchers tendency to use different collective intelligence as the search methods to optimize complex engineering problems has increased because of the high performance of this algorithms. Gravitational search algorithm (GSA) is among these algorithms. This algorithm is inspired by Newton's l...
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Najafabad Branch, Islamic Azad University
2013-04-01
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doaj-5c8468b8be0649cc8a116d8db909b06d2020-11-24T22:37:39ZengNajafabad Branch, Islamic Azad UniversityJournal of Intelligent Procedures in Electrical Technology2322-38712345-55942013-04-014144152Improved Gravitational Search Algorithm (GSA) Using Fuzzy LogicOmid Mokhlesi0Seyed Hamid Zahiri1Naser Mehrshad2Seyed Mohammad Razavi3khorasan Institute for Higher EducationUniversity of BirjandUniversity of BirjandUniversity of BirjandResearchers tendency to use different collective intelligence as the search methods to optimize complex engineering problems has increased because of the high performance of this algorithms. Gravitational search algorithm (GSA) is among these algorithms. This algorithm is inspired by Newton's laws of physics and gravitational attraction. Random masses are agents who have searched for the space. This paper presents a new Fuzzy Population GSA model called FPGSA. The proposed method is a combination of parametric fuzzy controller and gravitational search algorithm. The space being searched using this combined reasonable and accurate method. In the collective intelligence algorithms, population size influences the final answer so that for a large population, a better response is obtained but the algorithm execution time is longer. To overcome this problem, a new parameter called the dispersion coefficient is added to the algorithm. Implementation results show that by controlling this factor, system performance can be improved.http://jipet.iaun.ac.ir/pdf_4168_928ea1d91db433e1fa4e6225d395cd0d.htmlParametric fuzzy controllerGravitational search algorithm (GSA)Scattering coefficientFuzzy Population model |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Omid Mokhlesi Seyed Hamid Zahiri Naser Mehrshad Seyed Mohammad Razavi |
spellingShingle |
Omid Mokhlesi Seyed Hamid Zahiri Naser Mehrshad Seyed Mohammad Razavi Improved Gravitational Search Algorithm (GSA) Using Fuzzy Logic Journal of Intelligent Procedures in Electrical Technology Parametric fuzzy controller Gravitational search algorithm (GSA) Scattering coefficient Fuzzy Population model |
author_facet |
Omid Mokhlesi Seyed Hamid Zahiri Naser Mehrshad Seyed Mohammad Razavi |
author_sort |
Omid Mokhlesi |
title |
Improved Gravitational Search Algorithm (GSA) Using Fuzzy Logic |
title_short |
Improved Gravitational Search Algorithm (GSA) Using Fuzzy Logic |
title_full |
Improved Gravitational Search Algorithm (GSA) Using Fuzzy Logic |
title_fullStr |
Improved Gravitational Search Algorithm (GSA) Using Fuzzy Logic |
title_full_unstemmed |
Improved Gravitational Search Algorithm (GSA) Using Fuzzy Logic |
title_sort |
improved gravitational search algorithm (gsa) using fuzzy logic |
publisher |
Najafabad Branch, Islamic Azad University |
series |
Journal of Intelligent Procedures in Electrical Technology |
issn |
2322-3871 2345-5594 |
publishDate |
2013-04-01 |
description |
Researchers tendency to use different collective intelligence as the search methods to optimize complex engineering problems has increased because of the high performance of this algorithms. Gravitational search algorithm (GSA) is among these algorithms. This algorithm is inspired by Newton's laws of physics and gravitational attraction. Random masses are agents who have searched for the space. This paper presents a new Fuzzy Population GSA model called FPGSA. The proposed method is a combination of parametric fuzzy controller and gravitational search algorithm. The space being searched using this combined reasonable and accurate method. In the collective intelligence algorithms, population size influences the final answer so that for a large population, a better response is obtained but the algorithm execution time is longer. To overcome this problem, a new parameter called the dispersion coefficient is added to the algorithm. Implementation results show that by controlling this factor, system performance can be improved. |
topic |
Parametric fuzzy controller Gravitational search algorithm (GSA) Scattering coefficient Fuzzy Population model |
url |
http://jipet.iaun.ac.ir/pdf_4168_928ea1d91db433e1fa4e6225d395cd0d.html |
work_keys_str_mv |
AT omidmokhlesi improvedgravitationalsearchalgorithmgsausingfuzzylogic AT seyedhamidzahiri improvedgravitationalsearchalgorithmgsausingfuzzylogic AT nasermehrshad improvedgravitationalsearchalgorithmgsausingfuzzylogic AT seyedmohammadrazavi improvedgravitationalsearchalgorithmgsausingfuzzylogic |
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1725716122868645888 |