2021 5th IEEE International Conference on Cybernetics (CYBCONF)最新文献

筛选

英文中文

Towards Understanding The Space of Unrobust Features of Neural Networks 对神经网络非鲁棒特征空间的认识

2021 5th IEEE International Conference on Cybernetics (CYBCONF) Pub Date : 2021-06-08 DOI: 10.1109/CYBCONF51991.2021.9464137

Bingli Liao, Takahiro Kanzaki, Danilo Vasconcellos Vargas

引用次数: 1

A Proposal of Interactive Tabu Search for Creating Beverage by Blending Source Juices 一种混合原汁饮料的交互式禁忌搜索方法

2021 5th IEEE International Conference on Cybernetics (CYBCONF) Pub Date : 2021-06-08 DOI: 10.1109/CYBCONF51991.2021.9464140

M. Fukumoto, Gan Haoran, Y. Hanada

引用次数: 2

Preliminary Results for Subpopulation Algorithm Based on Novelty (SAN) Compared with the State of the Art 基于新颖性(SAN)的亚种群算法与现有算法比较的初步结果

2021 5th IEEE International Conference on Cybernetics (CYBCONF) Pub Date : 2021-06-08 DOI: 10.1109/CYBCONF51991.2021.9464153

Yuzi Jiang, Danilo Vasconcellos Vargas

{"title":"Preliminary Results for Subpopulation Algorithm Based on Novelty (SAN) Compared with the State of the Art","authors":"Yuzi Jiang, Danilo Vasconcellos Vargas","doi":"10.1109/CYBCONF51991.2021.9464153","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464153","url":null,"abstract":"Subpopulation algorithm based on novelty (SAN) has been investigated for some time and proved that it can be used for multi-objective optimization problems. It outperforms subpopulation algorithm based on general differential evolution (SAGDE) under the same framework, which highlights its special intrinsic mechanism. This intrinsic mechanism has something in common with some state-of-the-art multi-objective optimization algorithms. However, SAN has not yet proved its ability to be better than these algorithms and has not proven its ability to optimize problems with more than 5 objectives. In this paper, the advantage of SAN over other subpopulation algorithms, i.e., novelty search, is presented in detail. The similarities and differences between the intrinsic mechanisms of SAN, nondominated sorting genetic algorithm series (NSGAs) and multi-objective evolutionary algorithm based on decomposition (MOEA/D) are also analyzed. Finally, these three algorithms are evaluated on several well-known benchmark problems with more than two objectives. The result shows SAN surpassed NSGA-III (latest version in NSGAs) in 20 out of the 32 problems, surpassed MOEA/D in 26 problems in 10 runs, which preliminary proved it surpasses the State-of-the-Art.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131228890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

首页上一页