Development of Discrete-Cockroach Algorithm (DCA) for Feature Selection Optimization

Y. Hendrawan, Muchnuria Rachmawati, M. R. Fauzy
{"title":"Development of Discrete-Cockroach Algorithm (DCA) for Feature Selection Optimization","authors":"Y. Hendrawan, Muchnuria Rachmawati, M. R. Fauzy","doi":"10.11591/EECSI.V5.1639","DOIUrl":null,"url":null,"abstract":"One of the recently proposed algorithms in the field of bio-inspired algorithm is the Hungry Roach Infestation Optimization (HRIO) algorithm. Haven has developed optimization algorithms HRIO that is inspired by recent discoveries in the social behaviour of cockroaches. Result showed that HRIO was effective at finding the global optima of a suite of test functions. However, there is no researcher who has observed HRIO for solving discrete problems. Therefore, we try to develop a discrete-cockroach algorithm (DCA) as the modification of HRIO for solving discrete optimization problem. We test the algorithm to solve bio-computation problem using single and multi-objectives optimization. The results showed DCA has better performance compared to the existed bio-inspired optimization algorithms such as genetic algorithms (GA) and discrete-particle swarm optimization (discrete-PSO).","PeriodicalId":20498,"journal":{"name":"Proceeding of the Electrical Engineering Computer Science and Informatics","volume":"34 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceeding of the Electrical Engineering Computer Science and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11591/EECSI.V5.1639","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

One of the recently proposed algorithms in the field of bio-inspired algorithm is the Hungry Roach Infestation Optimization (HRIO) algorithm. Haven has developed optimization algorithms HRIO that is inspired by recent discoveries in the social behaviour of cockroaches. Result showed that HRIO was effective at finding the global optima of a suite of test functions. However, there is no researcher who has observed HRIO for solving discrete problems. Therefore, we try to develop a discrete-cockroach algorithm (DCA) as the modification of HRIO for solving discrete optimization problem. We test the algorithm to solve bio-computation problem using single and multi-objectives optimization. The results showed DCA has better performance compared to the existed bio-inspired optimization algorithms such as genetic algorithms (GA) and discrete-particle swarm optimization (discrete-PSO).
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
特征选择优化的离散蟑螂算法(DCA)的发展
最近在仿生算法领域提出的算法之一是饥饿蟑螂入侵优化算法(HRIO)。Haven开发了优化算法HRIO,其灵感来自于最近对蟑螂社会行为的发现。结果表明,该方法能够有效地找到一组测试函数的全局最优解。然而,还没有研究者观察到HRIO用于解决离散问题。因此,我们尝试发展一种离散蟑螂算法(DCA),作为HRIO的改进来解决离散优化问题。通过单目标优化和多目标优化,对该算法进行了测试,以解决生物计算问题。结果表明,与遗传算法(GA)和离散粒子群优化算法(discrete-particle swarm optimization, pso)等已有的仿生优化算法相比,DCA具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Estimated Profits of Rengginang Lorjuk Madura by Used Comparison of Holt-Winter and Moving Average Water Contents and Monoglycerides as Development Role of Biodiesel Standard in Indonesia for B30 Implementation Image Restoration Effect on DCT High Frequency Removal and Wiener Algorithm for Detecting Facial Key Points RAIKU: E-Commerce App Using Laravel Probabilistic Programming with Piecewise Objective Function for Solving Supplier Selection Problem with Price Discount and Probabilistic Demand
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1