亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

The Use of Machine Learning to Predict Steel Properties – A Review on the Latest Works

人工智能 计算机科学 人工智能应用 机器学习
作者
Adriana da Cunha Rocha,Pedro Enrique Monforte Brandão Marques
出处
期刊:IntechOpen eBooks [IntechOpen]
标识
DOI:10.5772/intechopen.1004639
摘要

Artificial Intelligence [AI] has been of great discussion lately and one can perceive its use in many aspects of modern life. In science, and more specifically in Materials Sciences, AI has been employed for many different applications. Machine Learning (ML) has been historically linked to Artificial Intelligence (AI) for many decades. Some basic concepts of ML can be traced from the 1930s, but it was only during the 1980s and 1990s that ML really started to be used in a stronger and well-organized fashion, due to the development of more efficient algorithms from better and more robust data processing machines. This chapter presents a review on the recent works of distinct research groups that have been using Machine Learning [ML], which is one of many different methods of AI, as a tool for predicting steel properties. A brief definition of ML is given at the beginning of the chapter, followed by some of the most relevant examples of ML use to exemplify the power of this AI method for the development of steel engineering.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
麻辣薯条完成签到,获得积分10
1秒前
科研通AI2S应助科研通管家采纳,获得10
1秒前
bkagyin应助科研通管家采纳,获得10
1秒前
Criminology34应助科研通管家采纳,获得10
1秒前
Criminology34应助科研通管家采纳,获得10
1秒前
Criminology34应助科研通管家采纳,获得10
1秒前
时尚身影完成签到,获得积分10
4秒前
CR7应助Yini采纳,获得20
5秒前
流苏2完成签到,获得积分10
8秒前
Lucas应助买三个包子吧采纳,获得10
24秒前
wq发布了新的文献求助10
30秒前
在水一方应助wq采纳,获得10
36秒前
BTW完成签到,获得积分10
43秒前
甜橙完成签到 ,获得积分10
44秒前
45秒前
年少完成签到 ,获得积分10
59秒前
科目三应助可靠的寒风采纳,获得10
1分钟前
胖胖的江鸟完成签到 ,获得积分10
1分钟前
黄淳完成签到 ,获得积分10
1分钟前
1分钟前
随想完成签到,获得积分10
1分钟前
wq发布了新的文献求助10
1分钟前
1分钟前
Owen应助昭昭采纳,获得10
1分钟前
Hello应助Developing_human采纳,获得10
1分钟前
香蕉觅云应助wq采纳,获得10
1分钟前
1分钟前
明月清风完成签到,获得积分10
2分钟前
科研通AI2S应助科研通管家采纳,获得10
2分钟前
SciGPT应助科研通管家采纳,获得10
2分钟前
2分钟前
Criminology34应助科研通管家采纳,获得10
2分钟前
Criminology34应助科研通管家采纳,获得10
2分钟前
陈鑫发布了新的文献求助10
2分钟前
量子星尘发布了新的文献求助10
2分钟前
CC完成签到 ,获得积分10
2分钟前
2分钟前
2分钟前
2分钟前
陈鑫完成签到,获得积分20
2分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Binary Alloy Phase Diagrams, 2nd Edition 8000
Building Quantum Computers 800
Translanguaging in Action in English-Medium Classrooms: A Resource Book for Teachers 700
Natural Product Extraction: Principles and Applications 500
Exosomes Pipeline Insight, 2025 500
Red Book: 2024–2027 Report of the Committee on Infectious Diseases 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5664241
求助须知:如何正确求助?哪些是违规求助? 4859506
关于积分的说明 15107358
捐赠科研通 4822753
什么是DOI,文献DOI怎么找? 2581699
邀请新用户注册赠送积分活动 1535922
关于科研通互助平台的介绍 1494120