使用人工神经网络的软件工作量估算:当前实践综述

H. Hamza, Amr A. Kamel, K. M. Shams
{"title":"使用人工神经网络的软件工作量估算:当前实践综述","authors":"H. Hamza, Amr A. Kamel, K. M. Shams","doi":"10.1109/ITNG.2013.111","DOIUrl":null,"url":null,"abstract":"The value of Artificial Neural Networks (ANNs) methods in performing complicated pattern recognition and nonlinear estimation tasks has been demonstrated across an impressive spectrum of applications. ANNs methods are also used in software development process, since it is a complex environment with many interrelated factors affecting development effort and productivity. Accurate forecasting has proved difficult since many of these interrelationships are not fully understood. This paper provides an overview on the use Artificial Neural Networks methods to estimate the development effort for software development projects. In this survey an explanation, on why those methods are used and how accurate they are.","PeriodicalId":320262,"journal":{"name":"2013 10th International Conference on Information Technology: New Generations","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Software Effort Estimation Using Artificial Neural Networks: A Survey of the Current Practices\",\"authors\":\"H. Hamza, Amr A. Kamel, K. M. Shams\",\"doi\":\"10.1109/ITNG.2013.111\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The value of Artificial Neural Networks (ANNs) methods in performing complicated pattern recognition and nonlinear estimation tasks has been demonstrated across an impressive spectrum of applications. ANNs methods are also used in software development process, since it is a complex environment with many interrelated factors affecting development effort and productivity. Accurate forecasting has proved difficult since many of these interrelationships are not fully understood. This paper provides an overview on the use Artificial Neural Networks methods to estimate the development effort for software development projects. In this survey an explanation, on why those methods are used and how accurate they are.\",\"PeriodicalId\":320262,\"journal\":{\"name\":\"2013 10th International Conference on Information Technology: New Generations\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 10th International Conference on Information Technology: New Generations\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITNG.2013.111\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 10th International Conference on Information Technology: New Generations","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITNG.2013.111","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13

摘要

人工神经网络(ann)方法在执行复杂模式识别和非线性估计任务方面的价值已经在一系列令人印象深刻的应用中得到了证明。人工神经网络方法也用于软件开发过程,因为它是一个复杂的环境,有许多相互关联的因素影响开发工作和生产力。事实证明,准确的预测是困难的,因为许多这些相互关系没有得到充分了解。本文概述了使用人工神经网络方法来评估软件开发项目的开发工作量。在本调查中,解释了为什么使用这些方法以及它们的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Software Effort Estimation Using Artificial Neural Networks: A Survey of the Current Practices
The value of Artificial Neural Networks (ANNs) methods in performing complicated pattern recognition and nonlinear estimation tasks has been demonstrated across an impressive spectrum of applications. ANNs methods are also used in software development process, since it is a complex environment with many interrelated factors affecting development effort and productivity. Accurate forecasting has proved difficult since many of these interrelationships are not fully understood. This paper provides an overview on the use Artificial Neural Networks methods to estimate the development effort for software development projects. In this survey an explanation, on why those methods are used and how accurate they are.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A User-centric Approach towards Understanding the Influences of Social Tags Choices for Academic Papers Forecasting Wet Land Rice Production for Food Security A Study on the Bootstrapping Architectures for Scalable Private Reappearing Overlay Network Software Safety and Security for Programmable Logic Controllers Text-to-Onto Miner: A Concept Driven and Interval Controlled Ontology Builder
×
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