Hesitancy Set and Sub-optimum Analysis of Intuition

Abstract

The goal of this paper is to present a new model for, or rather a new way of thinking of human behaviors: sub-optimum analysis of intuition. We analyses the formation and variation of intuitions from the sub-optimum option of behavior attributes, and present the conception of hesitancy set, then propose that the rational standards of behavior selection is an effective control of intuitionistic process under perception angle, finally design the minimum hesitancy degree. In this paper we suggest a new intelligent technique called Trusted Hesitancy Reasoning. (THR) The main idea involves a dynamic adaptation of the sub-optimal number of neighbors by considering the distribution of distances between potential similar neighbors for intuitive action. In order to do this, our technique finds the sub-optimal distance threshold and selects similar neighbors satisfying the distance threshold criterion. The results of this paper show that the proposed technique outperforms those of many other methods, it overcomes the limitation of conventional intuitionist fuzzy set, and it provides improved uncertainty decision making.