机械加工过程中表面粗糙度测量建模的人工神经网络技术综述

A. Zain, H. Haron, S. Sharif
{"title":"机械加工过程中表面粗糙度测量建模的人工神经网络技术综述","authors":"A. Zain, H. Haron, S. Sharif","doi":"10.1109/AMS.2009.78","DOIUrl":null,"url":null,"abstract":"The former, which is defined as modeling of machining processes, is essential to provide the basic mathematical models for formulation of the certain process objective functions. With conventional approaches such as Statistical Regression technique, explicit models are developed that required complex physical understanding of the modeling process. With non conventional approaches or Artificial Intelligence techniques such as Artificial Neural Network, Fuzzy Logic and Genetic Algorithm based modeling, implicit model are created within the weight matrices of the net, rules and genes that is easier to be implemented. With the focus on surface roughness performance measure, this paper outlines and discusses the concept, application, abilities and limitations of Artificial Neural Network in the machining process modeling. Subsequently the future trend of Artificial Neural Network in modeling machining process is reported.","PeriodicalId":6461,"journal":{"name":"2009 Third Asia International Conference on Modelling & Simulation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":"{\"title\":\"Review of ANN Technique for Modeling Surface Roughness Performance Measure in Machining Process\",\"authors\":\"A. Zain, H. Haron, S. Sharif\",\"doi\":\"10.1109/AMS.2009.78\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The former, which is defined as modeling of machining processes, is essential to provide the basic mathematical models for formulation of the certain process objective functions. With conventional approaches such as Statistical Regression technique, explicit models are developed that required complex physical understanding of the modeling process. With non conventional approaches or Artificial Intelligence techniques such as Artificial Neural Network, Fuzzy Logic and Genetic Algorithm based modeling, implicit model are created within the weight matrices of the net, rules and genes that is easier to be implemented. With the focus on surface roughness performance measure, this paper outlines and discusses the concept, application, abilities and limitations of Artificial Neural Network in the machining process modeling. Subsequently the future trend of Artificial Neural Network in modeling machining process is reported.\",\"PeriodicalId\":6461,\"journal\":{\"name\":\"2009 Third Asia International Conference on Modelling & Simulation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"27\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Third Asia International Conference on Modelling & Simulation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AMS.2009.78\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Third Asia International Conference on Modelling & Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AMS.2009.78","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 27

摘要

前者定义为加工过程的建模,为确定加工过程的目标函数提供基本的数学模型。使用统计回归技术等传统方法,开发显式模型需要对建模过程进行复杂的物理理解。利用非常规方法或人工智能技术,如人工神经网络、模糊逻辑和基于遗传算法的建模,在网络、规则和基因的权重矩阵中创建隐式模型,更容易实现。本文以表面粗糙度性能测量为重点,概述并讨论了人工神经网络在加工过程建模中的概念、应用、能力和局限性。展望了人工神经网络在加工过程建模中的应用前景。
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
Review of ANN Technique for Modeling Surface Roughness Performance Measure in Machining Process
The former, which is defined as modeling of machining processes, is essential to provide the basic mathematical models for formulation of the certain process objective functions. With conventional approaches such as Statistical Regression technique, explicit models are developed that required complex physical understanding of the modeling process. With non conventional approaches or Artificial Intelligence techniques such as Artificial Neural Network, Fuzzy Logic and Genetic Algorithm based modeling, implicit model are created within the weight matrices of the net, rules and genes that is easier to be implemented. With the focus on surface roughness performance measure, this paper outlines and discusses the concept, application, abilities and limitations of Artificial Neural Network in the machining process modeling. Subsequently the future trend of Artificial Neural Network in modeling machining process is reported.
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 Transparent Classification Model Using a Hybrid Soft Computing Method Study on the Performance of Tag-Tag Collision Avoidance Algorithms in RFID Systems Cross Layer Design of Wireless LAN for Telemedicine Application Jawi Character Speech-to-Text Engine Using Linear Predictive and Neural Network for Effective Reading Advances in Supply Chain Simulation
×
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