Fundamental Categories of Artificial Neural Networks

Arunaben Prahladbhai Gurjar, S. Patel
{"title":"Fundamental Categories of Artificial Neural Networks","authors":"Arunaben Prahladbhai Gurjar, S. Patel","doi":"10.4018/978-1-7998-4042-8.CH003","DOIUrl":null,"url":null,"abstract":"The new era of the world uses artificial intelligence (AI) and machine learning. The combination of AI and machine learning is called artificial neural network (ANN). Artificial neural network can be used as hardware or software-based components. Different topology and learning algorithms are used in artificial neural networks. Artificial neural network works similarly to the functionality of the human nervous system. ANN is working as a nonlinear computing model based on activities performed by human brain such as classification, prediction, decision making, visualization just by considering previous experience. ANN is used to solve complex, hard-to-manage problems by accruing knowledge about the environment. There are different types of artificial neural networks available in machine learning. All types of artificial neural networks work based of mathematical operation and require a set of parameters to get results. This chapter gives overview on the various types of neural networks like feed forward, recurrent, feedback, classification-predication.","PeriodicalId":198666,"journal":{"name":"Applications of Artificial Neural Networks for Nonlinear Data","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applications of Artificial Neural Networks for Nonlinear Data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/978-1-7998-4042-8.CH003","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

The new era of the world uses artificial intelligence (AI) and machine learning. The combination of AI and machine learning is called artificial neural network (ANN). Artificial neural network can be used as hardware or software-based components. Different topology and learning algorithms are used in artificial neural networks. Artificial neural network works similarly to the functionality of the human nervous system. ANN is working as a nonlinear computing model based on activities performed by human brain such as classification, prediction, decision making, visualization just by considering previous experience. ANN is used to solve complex, hard-to-manage problems by accruing knowledge about the environment. There are different types of artificial neural networks available in machine learning. All types of artificial neural networks work based of mathematical operation and require a set of parameters to get results. This chapter gives overview on the various types of neural networks like feed forward, recurrent, feedback, classification-predication.
人工神经网络的基本分类
新时代的世界使用人工智能(AI)和机器学习。人工智能和机器学习的结合被称为人工神经网络(ANN)。人工神经网络既可以作为基于硬件的组件,也可以作为基于软件的组件。人工神经网络采用了不同的拓扑结构和学习算法。人工神经网络的工作原理与人类神经系统的功能相似。人工神经网络是一种基于人类大脑活动的非线性计算模型,如分类、预测、决策、可视化等。人工神经网络通过积累有关环境的知识来解决复杂的、难以管理的问题。机器学习中有不同类型的人工神经网络。所有类型的人工神经网络都是基于数学运算,并需要一组参数来获得结果。本章概述了各种类型的神经网络,如前馈、循环、反馈、分类预测。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信