Fuzzy Sets Theory and Its Applications

Dear Colleagues,

The concept of fuzzy sets introduced by L.A. Zadeh in 1965 tried to extend the classical set theory. It is well-known that a classical set corresponds to an indicator function whose values are only taken to be 0 and 1. With the aid of membership functions associated with a fuzzy set, each element in a set allows one to take any values between 0 and 1 that can be treated as the degree of membership. This kind of imprecision draws forth a multitude of applications. This topic will focus on the original research that reflects the theoretical developments and applicable results.

The topics of interest include but are not limited to the following:

• Foundation of fuzzy sets (fuzzy arithmetic operations, extension principle, possibility measures, etc.).
• Fuzzy mathematics (fuzzy topology, fuzzy real analysis, fuzzy integral and differential equations, fuzzy metric spaces, fuzzy algebra, etc.). 
• Fuzzy logics (many-valued logics, type-2 fuzzy logics, intuitionistic fuzzy logics, etc.). 
• Fuzzy statistical analysis (fuzzy random variables, fuzzy regression analysis, fuzzy reliability analysis, fuzzy times series, fuzzy Markov process, etc.). 
• Hybrid systems (fuzzy control, fuzzy neural networks, genetic fuzzy systems, fuzzy intelligent systems, fuzzy biomedical systems, fuzzy chaotic systems, fuzzy information systems, etc.). 
• Nature of computation (ant colony optimization, artificial immune systems, genetic algorithms, particle swarm intelligence, simulated annealing, tabu search, etc.). 
• Computational intelligence (artificial intelligence, approximate reasoning, expert systems, machine learning, support vector machines, robotics, image processing, pattern recognition, information retrieval, etc.). 
• Operations research and management sciences (fuzzy games theory, fuzzy inventory models, fuzzy queueing theory, fuzzy scheduling problems, fuzzy optimization, fuzzy decision making, fuzzy data mining, fuzzy clustering, stochastic optimization, financial derivatives, uncertainty modeling, etc.).

Prof. Dr. Hsien-Chung Wu
Prof. Dr. Ziye Zhang
Dr. Rongrong Yu
Topic Editors