An empirical study on influence of approximation approaches on enhancing fireworks algorithm
This paper presents an empirical study on the influence of approximation approaches on accelerating the fireworks algorithm search by elite strategy. In this study, we use three sampling data methods to approximate fitness landscape, i.e. the best fitness sampling method, the sampling distance near...
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| creator | Yan Pei Shaoqiu Zheng Ying Tan Takagi, Hideyuki |
| description | This paper presents an empirical study on the influence of approximation approaches on accelerating the fireworks algorithm search by elite strategy. In this study, we use three sampling data methods to approximate fitness landscape, i.e. the best fitness sampling method, the sampling distance near the best fitness individual sampling method and the random sampling method. For each approximation methods, we conduct a series of combinative evaluations with the different sampling method and sampling number for accelerating fireworks algorithm. The experimental evaluations on benchmark functions show that this elite strategy can enhance the fireworks algorithm search capability effectively. We also analyze and discuss the related issues on the influence of approximation model, sampling method, and sampling number on the fireworks algorithm acceleration performance. |
| doi_str_mv | 10.1109/ICSMC.2012.6377916 |
| format | Conference Proceeding |
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In this study, we use three sampling data methods to approximate fitness landscape, i.e. the best fitness sampling method, the sampling distance near the best fitness individual sampling method and the random sampling method. For each approximation methods, we conduct a series of combinative evaluations with the different sampling method and sampling number for accelerating fireworks algorithm. The experimental evaluations on benchmark functions show that this elite strategy can enhance the fireworks algorithm search capability effectively. 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We also analyze and discuss the related issues on the influence of approximation model, sampling method, and sampling number on the fireworks algorithm acceleration performance.</description><subject>Acceleration</subject><subject>Approximation</subject><subject>Approximation algorithms</subject><subject>Benchmark testing</subject><subject>Elite Strategy</subject><subject>Fireworks Algorithm</subject><subject>Fitness Landscape</subject><subject>Least squares approximation</subject><subject>Sampling methods</subject><subject>Sparks</subject><issn>1062-922X</issn><issn>2577-1655</issn><isbn>9781467317139</isbn><isbn>1467317136</isbn><isbn>1467317144</isbn><isbn>9781467317122</isbn><isbn>9781467317146</isbn><isbn>1467317128</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1kNtKw0AYhNcT2Na-gN7sCyTu_-8pe1mCh0LFCxW8EMom2bSr6SZsUrRvb9V6NQzfMAxDyCWwFICZ63n-9JCnyABTxbU2oI7IGITSHDQIcUxGKLVOQEl5QqZGZ_-Mm1MyAqYwMYiv52Tc9--MIROQjcjbLFC36Xz0pW1oP2yrHW0D9aFuti6UjrY1tV0X2y-_sYPfo19ny7Xrf4IurG0ofVjR2kf32caPntpm1UY_rDcX5Ky2Te-mB52Ql9ub5_w-WTzezfPZIvGYySExVgrUEnlmORaCaVm5DBAKWVhXSadrJqwSleJGW6xcqTUWyGoFYLlQjE_I1V-vd84tu7ifGnfLw0v8G7ftWJQ</recordid><startdate>201210</startdate><enddate>201210</enddate><creator>Yan Pei</creator><creator>Shaoqiu Zheng</creator><creator>Ying Tan</creator><creator>Takagi, Hideyuki</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201210</creationdate><title>An empirical study on influence of approximation approaches on enhancing fireworks algorithm</title><author>Yan Pei ; Shaoqiu Zheng ; Ying Tan ; Takagi, Hideyuki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i285t-9a54275238a32b4075de8121b5baed5e7f04a64d6397a2dec772b20f611a34603</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Acceleration</topic><topic>Approximation</topic><topic>Approximation algorithms</topic><topic>Benchmark testing</topic><topic>Elite Strategy</topic><topic>Fireworks Algorithm</topic><topic>Fitness Landscape</topic><topic>Least squares approximation</topic><topic>Sampling methods</topic><topic>Sparks</topic><toplevel>online_resources</toplevel><creatorcontrib>Yan Pei</creatorcontrib><creatorcontrib>Shaoqiu Zheng</creatorcontrib><creatorcontrib>Ying Tan</creatorcontrib><creatorcontrib>Takagi, Hideyuki</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yan Pei</au><au>Shaoqiu Zheng</au><au>Ying Tan</au><au>Takagi, Hideyuki</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>An empirical study on influence of approximation approaches on enhancing fireworks algorithm</atitle><btitle>2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)</btitle><stitle>ICSMC</stitle><date>2012-10</date><risdate>2012</risdate><spage>1322</spage><epage>1327</epage><pages>1322-1327</pages><issn>1062-922X</issn><eissn>2577-1655</eissn><isbn>9781467317139</isbn><isbn>1467317136</isbn><eisbn>1467317144</eisbn><eisbn>9781467317122</eisbn><eisbn>9781467317146</eisbn><eisbn>1467317128</eisbn><abstract>This paper presents an empirical study on the influence of approximation approaches on accelerating the fireworks algorithm search by elite strategy. In this study, we use three sampling data methods to approximate fitness landscape, i.e. the best fitness sampling method, the sampling distance near the best fitness individual sampling method and the random sampling method. For each approximation methods, we conduct a series of combinative evaluations with the different sampling method and sampling number for accelerating fireworks algorithm. The experimental evaluations on benchmark functions show that this elite strategy can enhance the fireworks algorithm search capability effectively. We also analyze and discuss the related issues on the influence of approximation model, sampling method, and sampling number on the fireworks algorithm acceleration performance.</abstract><pub>IEEE</pub><doi>10.1109/ICSMC.2012.6377916</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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| identifier | ISSN: 1062-922X |
| ispartof | 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2012, p.1322-1327 |
| issn | 1062-922X 2577-1655 |
| language | eng |
| recordid | cdi_ieee_primary_6377916 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Acceleration Approximation Approximation algorithms Benchmark testing Elite Strategy Fireworks Algorithm Fitness Landscape Least squares approximation Sampling methods Sparks |
| title | An empirical study on influence of approximation approaches on enhancing fireworks algorithm |
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