We extend Knuth's 16 Boolean binary logic operators to fuzzy logic and neutrosophic logic binary operators. Then we generalize them to n-ary fuzzy logic and neutrosophic logic operators using the smarandache codification of the Venn diagram and a defined vector neutrosophic law. In such way, new operators in neutrosophic logic/set/probability are built. Introduction. For the beginning let’s con...

A method for response integration in modular neural networks with type-2 fuzzy logic for biometric systems p. 5 Evolving type-2 fuzzy logic controllers for autonomous mobile robots p. 16 Adaptive type-2 fuzzy logic for intelligent home environment p. 26 Interval type-1 non-singleton type-2 TSK fuzzy logic systems using the hybrid training method RLS-BP p. 36 An efficient computational method to...

Fuzzy logic has a considerable success in the area of applications. However, this active growth in the implementation in applied electronic devices has not always been accompanied by a discussion about the theoretical grounds underlying those uses. This paper deals with some theoretical aspects that seem convenient to discuss for the purpose of clarifying the status of fuzzy logic, to get into ...

The introduction of fuzzy logic in 1965 has been one of the main advancements in the last several decades in different subjects and especially in control theory [1]. Fuzzy logic has given large deals to reasoning, and clearly, shows its applicability in many areas to solve different problems concerning approximate reasoning. However, in large measure what remains unrecognized is that fuzzy logi...

I develop a new game-theoretic approach based, not on conventional Boolean two-valued logic, but instead on linguistic fuzzy logic which admits linguistic truth values. A linguistic fuzzy game is defined with linguistic fuzzy strategies, linguistic fuzzy preferences, and the rules of reasoning and inferences of the game operate according to linguistic fuzzy logic, not Boolean logic. This leads ...

the goal of this paper is to show how the concept of fuzzy logic can be used to establish a degree to which an investment project belongs to a class of risk. also, the probability of the fuzzy event is presented and is ap-plied to calculate the probability of the fuzzy event “the project x is a good investment”. this process has to enable the decision maker to compare several alternative invest...