找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Machine Learning for Advanced Functional Materials; Nirav Joshi,Vinod Kushvaha,Priyanka Madhushri Book 2023 The Editor(s) (if applicable)

[复制链接]
查看: 46426|回复: 52
发表于 2025-3-21 18:56:54 | 显示全部楼层 |阅读模式
书目名称Machine Learning for Advanced Functional Materials
编辑Nirav Joshi,Vinod Kushvaha,Priyanka Madhushri
视频video
概述Highlights machine learning methods and their applications in material science and nanotechnologies.Covers machine learning in modeling as well as data analyses on material characteristics.Provides a
图书封面Titlebook: Machine Learning for Advanced Functional Materials;  Nirav Joshi,Vinod Kushvaha,Priyanka Madhushri Book 2023 The Editor(s) (if applicable)
描述.This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. It provides an introduction to the field and for those who wish to explore machine learning in modeling as well as conduct data analyses of material characteristics. The book discusses ways to enhance the material’s electrical and mechanical properties based on available regression methods for supervised learning and optimization of material attributes. In summary, the growing interest among academics and professionals in the field of machine learning methods in functional nanomaterials such as sensors, solar cells, and photocatalysis is the driving force for behind this book. This is a comprehensive scientific reference book on machine learning for advanced functional materials and provides an in-depth examination of recent achievements in material science by focusing on topical issues using machine learning methods..
出版日期Book 2023
关键词Thermoelectric materials; Sensors and biosensors; Polymer solar cell; Biomarker identification; Cancer r
版次1
doihttps://doi.org/10.1007/978-981-99-0393-1
isbn_softcover978-981-99-0395-5
isbn_ebook978-981-99-0393-1
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

书目名称Machine Learning for Advanced Functional Materials影响因子(影响力)




书目名称Machine Learning for Advanced Functional Materials影响因子(影响力)学科排名




书目名称Machine Learning for Advanced Functional Materials网络公开度




书目名称Machine Learning for Advanced Functional Materials网络公开度学科排名




书目名称Machine Learning for Advanced Functional Materials被引频次




书目名称Machine Learning for Advanced Functional Materials被引频次学科排名




书目名称Machine Learning for Advanced Functional Materials年度引用




书目名称Machine Learning for Advanced Functional Materials年度引用学科排名




书目名称Machine Learning for Advanced Functional Materials读者反馈




书目名称Machine Learning for Advanced Functional Materials读者反馈学科排名




单选投票, 共有 0 人参与投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用户组没有投票权限
发表于 2025-3-21 21:16:24 | 显示全部楼层
Machine Learning for Advanced Functional Materials
发表于 2025-3-22 03:01:38 | 显示全部楼层
发表于 2025-3-22 05:18:18 | 显示全部楼层
发表于 2025-3-22 11:33:18 | 显示全部楼层
Tulsi Satyavir Dabodiya,Jayant Kumar,Arumugam Vadivel Murugan
发表于 2025-3-22 16:23:32 | 显示全部楼层
发表于 2025-3-22 21:04:29 | 显示全部楼层
发表于 2025-3-22 23:40:52 | 显示全部楼层
Shirong Huang,Alexander Croy,Bergoi Ibarlucea,Gianaurelio Cunibertin 2.2.2 presents an overview of how Hoey’s (1991, 1995) ideas about . evolved and were tested and then described in . (2005). Thirdly, in Sections 2.3 and 2.4, the psychological concept of priming, first mention by Quillian (1961) is discussed. Then Section 2.5 looks at priming and the new options t
发表于 2025-3-23 04:44:55 | 显示全部楼层
发表于 2025-3-23 06:32:28 | 显示全部楼层
Purvi Bhatt,Neha Singh,Sumit Chaudharyitions (Vossen 1990b), statistical programs to deal with the distributional properties of lexical items in large corpora (Church & Hanks 1990) etc. At the same time this kind of massive data-acquisition should be made sensitive to the borders between perceptual experience, lexical knowledge and expe
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-30 09:41
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表