The concepts of Soft Computing introduced by Lotfi A. Zadeh in 1991 has integrated different methodologies and approaches, as: fuzzy set theory, fuzzy logic, approximate reasoning, linguistic expression of knowledge, probabilistic reasoning, and others for solving problems of complex systems in the way similar to human perception, recognition and solving problem methods. Linguistic fuzzy modell...

One of the most controversial issues in uncertainty modelling and information sciences is the relationship between probability theory and fuzzy sets. This paper is meant to survey the literature pertaining to this debate, and to try to overcome misunderstandings and to supply access to many basic references that have addressed the "probability versus fuzzy set" challenge. This problem has not a...

In this paper the theory of fuzzy logic is mixed with the theory of Markov systems and the abstraction of a Markov system with fuzzy states introduced. The notions such as fuzzy transient, fuzzy recurrent etc., were introduced. The results based on these notions are introduced.

Using intelligent techniques to perform radio resource management is an effective method. This paper proposes neural fuzzy control for radio resource management in hierarchical cellular systems supporting multimedia services. A neural fuzzy resource manager (NFRM) is designed, which mainly contains a neural fuzzy channel allocation processor (NFCAP), and NFCAP is in a two-layer architecture: a ...

Computing with Words is an emerging paradigm in knowledge representation and information processing. It provides a mathematical model to represent the meaning of imprecise words and phrases in natural language and introduces advanced techniques to perform reasoning on inexact knowledge. Since its introduction, there have been many studies on computing with words but mostly from the theoretical ...

Fuzzy inference has been proven a candidate technology for context recognition systems. In comparison to probability theory, its advantage is its more natural mapping of phenomena of the real world as context. This paper reports on our experience with building and using monolithic fuzzy-based systems (a TSK-FIS) to recognize real-world events and to classify these events into several categories...

Fuzzy inference has been proven a candidate technology for context recognition systems. In comparison to probability theory, its advantage is its more natural mapping of phenomena of the real world as context. This paper reports on our experience with an building and using of monolithic fuzzy based system (a TSK-FIS) to recognize realworld events and to classify these events into several catego...

Non-additive measures, also known as fuzzy capacities, and monotonic games, are increasingly used in different fields. Applications have been built within computer science artificial intelligence related to e.g., decision making, image processing, machine learning for both classification, regression. Tools measure identification built. In short, non-additive measures more general than additive ...