Suppr超能文献

一种基于中智集和TODIM的异构多属性案例检索方法用于紧急情况

A heterogeneous multi-attribute case retrieval method based on neutrosophic sets and TODIM for emergency situations.

作者信息

Zhang Kai, Zheng Jing, Wang Ying-Ming

机构信息

College of Information and Intelligent Transportation, Fujian Chuanzheng Communications College, Fuzhou, 350007 Fujian China.

College of Electronics and Information Science, Fujian Jiangxia University, Fuzhou, 350108 Fujian China.

出版信息

Appl Intell (Dordr). 2022;52(13):15177-15192. doi: 10.1007/s10489-022-03240-w. Epub 2022 Mar 11.

Abstract

Heterogeneous multi-attribute case retrieval is a crucial step in generating emergency alternatives during the course of emergency decision making (EDM) by referring to historical cases. This paper develops a heterogeneous multi-attribute case retrieval method for EDM that considers five attribute formats: crisp numbers, interval numbers, intuitionistic fuzzy numbers, single-valued neutrosophic numbers (SvNNs), and interval-valued neutrosophic numbers (IvNNs). First, we propose a similarity measurement of IvNNs and calculate the attribute similarities for the five attribute formats. The attribute weights are established using an optimal model. Next, the case similarities are calculated and the set of the similar historical cases is constructed. Furthermore, the evaluated information based on heterogeneous multi-attribute from similar historical cases is provided, and the calculation method for the evaluation of utility based on TODIM (an acronym for interactive and multi-criteria decision-making in Portugese) is proposed. The most suitable historical case is determined based on the case similarity and the evaluated utility. From this, the emergency alternative is generated. Finally, we demonstrate the efficacy of the proposed method with a case study and conduct comparisons against the performance of existing methods to assess the validity and superiority of the proposed method.

摘要

异构多属性案例检索是在应急决策(EDM)过程中通过参考历史案例生成应急方案的关键步骤。本文针对应急决策开发了一种异构多属性案例检索方法,该方法考虑了五种属性格式:清晰数、区间数、直觉模糊数、单值中智数(SvNNs)和区间值中智数(IvNNs)。首先,我们提出了区间值中智数的相似度度量,并计算了五种属性格式的属性相似度。使用一个优化模型确定属性权重。接下来,计算案例相似度并构建相似历史案例集。此外,提供了基于相似历史案例的异构多属性评估信息,并提出了基于TODIM(葡萄牙语中交互式多准则决策的首字母缩写)的效用评估计算方法。根据案例相似度和评估效用确定最合适的历史案例。由此生成应急方案。最后,我们通过一个案例研究证明了所提方法的有效性,并与现有方法的性能进行比较,以评估所提方法的有效性和优越性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bb/8916794/9181b7fa3479/10489_2022_3240_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验