期刊名称：IAENG International Journal of Computer Science
印刷版ISSN：1819-656X
电子版ISSN：1819-9224
出版年度：2020
卷号：47
期号：2
语种：English
出版社：IAENG - International Association of Engineers
摘要：The computing with Words (CW) is a well known soft computing method to find the solutions of many decision making problems in real life scenarios which consists of selective information used in natural language. CW is characterized by the human potentiality to do different types of physical and mental works or jobs without making any calculations or computations. Words are less accurate than numbers and words are used if exact numbers are unknown. Same word means different items to different person. There exists uncertainties associated with any word. Fuzzy set is generally used to model the words in the CW technique. The neutrosophic set is an extended version of fuzzy set. Here, we introduce a new idea of CW to model the words using neutrosophic set. In our proposed method, computation are done by words and words are translated to a mathematical model using neutrosophic set. The main objective of this paper is on CW based on neutrosophic set for taking subjective judgments. We call it as perceptual neutrosophic computing. An architecture is introduced for perceptual neutrosophic computing which we call perceptual neutrosophic computer (PNC). PNC has three components: encoder, CW engine for neutrosophic set and decoder. We have introduced a modified Kruskal’s algorithm to compute the minimum spanning tree (MST) of a neutrosophic graph. Human being describe those edge weights in real world problems using some terms, like, ’some’, ’small’, ’big’, ’large’, etc terms which do not provide any numbers. Those English terms are described here as words. A model of PNC is proposed to employ in our proposed method for solving this problem. The PNC model that is related with minimum spanning tree is defined as minimum spanning tree advisor (MSTA) and we have described the design of MSTA in detail in this study. We use a numerical example to describe the efficiency of our proposed algorithm.
关键词：Computing with Words;Kruskal’s algorithm;neutrosophic set
