New Distance Measures on Dual Hesitant Fuzzy Sets and Their Application in Pattern Recognition
Journal: Journal of Artificial Intelligence Practice (Vol.1, No. 1)Publication Date: 2016-12-31
Authors : Li Xin; Zhang Xiaohong;
Page : 8-13
Keywords : Dual hesitant fuzzy sets; Distance Measure; Hesitance degree; Pattern recognition.;
Abstract
The concept of dual hesitant fuzzy sets (DHFSs), which was first introduced as a new extension of fuzzy sets and hesitant fuzzy sets in 2012, is a useful tool to deal with the vagueness and ambiguity in many practical problems under hesitant fuzzy environment. Normally, we use the definition of distance to describe the relationship of two DHFSs. However, considering that the existing distance measures of DHFSs still have some major shortcomings, so in this paper, we firstly introduce a new concept –hesitance degree of each dual hesitant fuzzy element (DHFE) to these existing distance measures and then develop several novel distance measures in which both the values and the numbers of values of DHFE are taken into account. The properties of these new distance measures are discussed. Finally, we apply our proposed distance measures of DHFSs in pattern recognition making to illustrate their validity and applicability.
Other Latest Articles
- Urban Road Congestion Recognition Using Multi-Feature Fusion of Traffic Images
- An automatic people counting method of hotel dining with occlusion
- Compressive Sensing Based Data Collection in Wireless Sensor Networks
- Design and Realization of City Tourism Route Intelligent Programming System
- Study of logistics distribution route based on improved genetic algorithm and ant colony optimization algorithm
Last modified: 2017-03-29 07:13:15