{"title":"基于多样性信息的多因子进化算法求解多任务鲁棒影响最大化问题","authors":"Minghao Chen, Shuai Wang, Jiazhong Zhang","doi":"10.1080/09540091.2023.2275534","DOIUrl":null,"url":null,"abstract":"In recent years, one of the prominent research areas in the complex network field has been the Influence Maximization Problem. This problem focuses on selecting seed sets to achieve optimal informa...","PeriodicalId":50629,"journal":{"name":"Connection Science","volume":"21 1","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A multi-factorial evolutionary algorithm concerning diversity information for solving the multitasking Robust Influence Maximization Problem on networks\",\"authors\":\"Minghao Chen, Shuai Wang, Jiazhong Zhang\",\"doi\":\"10.1080/09540091.2023.2275534\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, one of the prominent research areas in the complex network field has been the Influence Maximization Problem. This problem focuses on selecting seed sets to achieve optimal informa...\",\"PeriodicalId\":50629,\"journal\":{\"name\":\"Connection Science\",\"volume\":\"21 1\",\"pages\":\"\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2023-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Connection Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/09540091.2023.2275534\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Connection Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/09540091.2023.2275534","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
A multi-factorial evolutionary algorithm concerning diversity information for solving the multitasking Robust Influence Maximization Problem on networks
In recent years, one of the prominent research areas in the complex network field has been the Influence Maximization Problem. This problem focuses on selecting seed sets to achieve optimal informa...
期刊介绍：
Connection Science is an interdisciplinary journal dedicated to exploring the convergence of the analytic and synthetic sciences, including neuroscience, computational modelling, artificial intelligence, machine learning, deep learning, Database, Big Data, quantum computing, Blockchain, Zero-Knowledge, Internet of Things, Cybersecurity, and parallel and distributed computing.
A strong focus is on the articles arising from connectionist, probabilistic, dynamical, or evolutionary approaches in aspects of Computer Science, applied applications, and systems-level computational subjects that seek to understand models in science and engineering.
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