文献类型：期刊文献

英文题名：Some distances, similarity and entropy measures for interval-valued neutrosophic sets and their relationship

作者：Ye, Jun[1];Du, Shigui[2]

机构：[1]Shaoxing Univ, Dept Elect & Informat Engn, 508 Huancheng West Rd, Shaoxing 312000, Zhejiang, Peoples R China;[2]Shaoxing Univ, Dept Civil Engn, 508 Huancheng West Rd, Shaoxing 312000, Zhejiang, Peoples R China

年份：2019

卷号：10

期号：2

起止页码：347

外文期刊名：INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS

收录：SCI-EXPANDED(收录号：WOS:000458539000010)、、EI(收录号：20190706489418)、Scopus(收录号：2-s2.0-85061216466)、WOS

基金：This paper was supported by the National Natural Science Foundation of China (No. 71471172).

语种：英文

外文关键词：Interval-valued neutrosophic set; Distance measure; Similarity measure; Entropy; Decision making

外文摘要：This paper proposes some new distance measures between interval-valued neutrosophic sets (IvNSs) and their similarity measures. Then, some entropy measures of IvNS based on the distances are proposed as the extension of the entropy measures of interval-valued intuitionistic fuzzy sets (IvIFSs). Also, we investigate the relationship between the presented entropy measures and the similarity measures for IvNSs. Finally, the comparison of the new entropy measures with existing entropy measures for IvNSs is given by the numerical and decision-making examples to demonstrate that the proposed new entropy measures for IvNSs are effective and reasonable and more intelligible in representing the degree of fuzziness of IvNSs than the existing ones.