人工智能在开发可持续智能工程系统中的未来:综述

Oghenevwegba T. Emuowhochere, E. Salawu, Samson O. Ongbali, O. Ajayi
{"title":"人工智能在开发可持续智能工程系统中的未来:综述","authors":"Oghenevwegba T. Emuowhochere, E. Salawu, Samson O. Ongbali, O. Ajayi","doi":"10.4028/p-0wnidr","DOIUrl":null,"url":null,"abstract":"Studying the behaviour of engineering systems and processes from the perspective of applications of artificial intelligence provides an invaluable reference to improve their productivity and industrial development at large. This study comprehensively unveiled the problems faced by engineering systems and how artificial intelligence could be deployed as a technique for the future advancement of the industry. A brief background of the application of artificial intelligence in some selected engineering fields revealed that insufficient operational and process data from both plants and processes are major problems causing the survival of sustainable intelligent systems thereby, leading to incessant system failure. Furthermore, it was equally discovered that artificial intelligent for specific application are based on the data obtained from such application. Thus, there is no universally agreed artificial intelligent for a specific application. This made it a bit complex in developing intelligent systems. Keywords: Artificial Neural Network, Applications, Engineering, Training, Data.","PeriodicalId":518456,"journal":{"name":"International Conference on Sustainable Engineering and Materials Development (ICSEMD)","volume":"58 6","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Future of Artificial Intelligence in Developing a Sustainable Intelligent Engineering Systems: A Review\",\"authors\":\"Oghenevwegba T. Emuowhochere, E. Salawu, Samson O. Ongbali, O. Ajayi\",\"doi\":\"10.4028/p-0wnidr\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Studying the behaviour of engineering systems and processes from the perspective of applications of artificial intelligence provides an invaluable reference to improve their productivity and industrial development at large. This study comprehensively unveiled the problems faced by engineering systems and how artificial intelligence could be deployed as a technique for the future advancement of the industry. A brief background of the application of artificial intelligence in some selected engineering fields revealed that insufficient operational and process data from both plants and processes are major problems causing the survival of sustainable intelligent systems thereby, leading to incessant system failure. Furthermore, it was equally discovered that artificial intelligent for specific application are based on the data obtained from such application. Thus, there is no universally agreed artificial intelligent for a specific application. This made it a bit complex in developing intelligent systems. Keywords: Artificial Neural Network, Applications, Engineering, Training, Data.\",\"PeriodicalId\":518456,\"journal\":{\"name\":\"International Conference on Sustainable Engineering and Materials Development (ICSEMD)\",\"volume\":\"58 6\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Sustainable Engineering and Materials Development (ICSEMD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4028/p-0wnidr\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Sustainable Engineering and Materials Development (ICSEMD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4028/p-0wnidr","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

从人工智能应用的角度研究工程系统和流程的行为,为提高其生产率和整个工业发展提供了宝贵的参考。这项研究全面揭示了工程系统所面临的问题,以及如何将人工智能作为一种技术加以应用,以促进未来工业的发展。对人工智能在一些选定工程领域的应用背景进行简要介绍后发现,来自工厂和流程的操作和流程数据不足是造成可持续智能系统生存的主要问题,从而导致系统故障不断。此外,研究还发现,人工智能的具体应用是以从这些应用中获得的数据为基础的。因此,对于特定的应用,并不存在普遍认同的人工智能。这使得开发智能系统变得有些复杂。关键词人工神经网络 应用 工程 训练 数据
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Future of Artificial Intelligence in Developing a Sustainable Intelligent Engineering Systems: A Review
Studying the behaviour of engineering systems and processes from the perspective of applications of artificial intelligence provides an invaluable reference to improve their productivity and industrial development at large. This study comprehensively unveiled the problems faced by engineering systems and how artificial intelligence could be deployed as a technique for the future advancement of the industry. A brief background of the application of artificial intelligence in some selected engineering fields revealed that insufficient operational and process data from both plants and processes are major problems causing the survival of sustainable intelligent systems thereby, leading to incessant system failure. Furthermore, it was equally discovered that artificial intelligent for specific application are based on the data obtained from such application. Thus, there is no universally agreed artificial intelligent for a specific application. This made it a bit complex in developing intelligent systems. Keywords: Artificial Neural Network, Applications, Engineering, Training, Data.
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
×
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