arXivDaily arXiv每日学术速递 周一至周五更新
北美退伍军人节(Veterans Day),12 日无更新
arXiv 2205.00829cs.AIcond-mat.mtrl-sci
收藏

材料信息学问题的容性优先视角功能分解树与系统描述

Function Decomposition Tree with Causality-First Perspective and Systematic Description of Problems in Materials Informatics

National Institute for Materials Science(国立材料科学研究所);Japan Advanced Institute of Science and Technology(日本北陆先端科学技术大学院大学);Tohoku University(东北大学);National Institute of Advanced Industrial Science and Technology(国立先进工业科学与技术研究所)

Hiori Kino, Hieu-Chi Dam, Takashi Miyake, Riichiro Mizoguchi

摘要:

由于材料信息学和其他因素,交叉学科正在蓬勃发展;需要一种系统的方式来表达知识并促进各领域科学家之间的交流。功能分解树就是这样一种表示方法,但领域科学家在构建功能分解树时遇到了困难,因此,本研究引用初学者在生成功能分解树时遇到的一般问题,并提出了一种新的功能分解表示方法。首先根据工作流的加工顺序进行分解,得到工作流的容限优先分解树。此外,我们开发了一个程序,执行自动转换使用的功能的cacquitity-first分解树。将该方法应用于材料信息学领域,验证了专家知识的系统表示及其实用性。

英文摘要:

As interdisciplinary science is flourishing because of materials informatics and additional factors; a systematic way is required for expressing knowledge and facilitating communication between scientists in various fields. A function decomposition tree is such a representation, but domain scientists face difficulty in constructing it. Thus, this study cites the general problems encountered by beginners in generating function decomposition trees and proposes a new function decomposition representation method based on a causality-first perspective for resolution of these problems. The causality-first decomposition tree was obtained from a workflow expressed according to the processing sequence. Moreover, we developed a program that performed automatic conversion using the features of the causality-first decomposition trees. The proposed method was applied to materials informatics to demonstrate the systematic representation of expert knowledge and its usefullness.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑