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Rough sets applied to the discovery of materials knowledge

机译:粗糙集应用于材料知识的发现

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摘要

The functional mapping of material structure to properties, processing, and use is the principal driver for all scientific and engineering endeavors. Given the high cost of experimentation and the computational intractability of ab initio materials research, more efficient and accurate predictions of yet-to-be-made materials is an equally prominent endeavor, if not a preeminent materials research frontier. Because of the vast amounts of information to be considered in the pursuit of either, the automation of search-based methods for augmenting more analytic approaches is receiving increasing attention. Given the computational challenges to automation and to retrieving data from complex databases, search-based methods offer an expeditious approach to providing a researcher both insight and perspective. Rough sets is discussed relative to these objectives, as is current research to address its limitations and difficulties in application. Several materials related examples are offered to illustrate the application of the method. (C) 1998 Elsevier Science S.A. All rights reserved. [References: 32]
机译:材料结构到特性,加工和使用的功能映射是所有科学和工程努力的主要动力。考虑到实验的高昂成本和从头开始的材料研究的计算难易性,即使不是卓越的材料研究前沿,对尚待生产的材料进行更有效,更准确的预测也是同样重要的工作。由于在选择任何一种方法时都需要考虑大量信息,因此基于搜索的方法用于增强更多分析方法的自动化受到了越来越多的关注。鉴于自动化和从复杂数据库中检索数据的计算难题,基于搜索的方法提供了一种快速的方法来为研究人员提供洞察力和视角。相对于这些目标,讨论了粗糙集,目前正在研究以解决其局限性和应用难题。提供了一些与材料相关的示例,以说明该方法的应用。 (C)1998 Elsevier Science S.A.保留所有权利。 [参考:32]

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