{"title":"建立多元静态回归问题的单前馈神经网络模型的一种新方法:加权初始化和构造算法","authors":"Ghabriel A. Gomes de Sá, C. Fontes, M. Embiruçu","doi":"10.1007/s12065-022-00813-z","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":46237,"journal":{"name":"Evolutionary Intelligence","volume":" ","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new method for building single feedforward neural network models for multivariate static regression problems: a combined weight initialization and constructive algorithm\",\"authors\":\"Ghabriel A. Gomes de Sá, C. Fontes, M. Embiruçu\",\"doi\":\"10.1007/s12065-022-00813-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":46237,\"journal\":{\"name\":\"Evolutionary Intelligence\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2022-12-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Evolutionary Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s12065-022-00813-z\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Evolutionary Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s12065-022-00813-z","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
A new method for building single feedforward neural network models for multivariate static regression problems: a combined weight initialization and constructive algorithm
期刊介绍:
This Journal provides an international forum for the timely publication and dissemination of foundational and applied research in the domain of Evolutionary Intelligence. The spectrum of emerging fields in contemporary artificial intelligence, including Big Data, Deep Learning, Computational Neuroscience bridged with evolutionary computing and other population-based search methods constitute the flag of Evolutionary Intelligence Journal.Topics of interest for Evolutionary Intelligence refer to different aspects of evolutionary models of computation empowered with intelligence-based approaches, including but not limited to architectures, model optimization and tuning, machine learning algorithms, life inspired adaptive algorithms, swarm-oriented strategies, high performance computing, massive data processing, with applications to domains like computer vision, image processing, simulation, robotics, computational finance, media, internet of things, medicine, bioinformatics, smart cities, and similar. Surveys outlining the state of art in specific subfields and applications are welcome.