In the early 1970s, fuzzy systems and fuzzy control theories added a new dimension to control systems engineering. From its beginnings as mostly heuristic and somewhat ad hoc, more recent and rigorous approaches to fuzzy control theory have helped make it an integral part of modern control theory an... Reflecting the tremendous advances that have taken place in the study of fuzzy set theory and...

the aim of this study is prospecting of iron and manganese in the balvard 1:100000 sheet which is situated in sanandaj - sirjan structural zone utilizing index overlay and fuzzy logic methods in the gis. in this study, the layers for integration, alterations, geological, geophysical, geochemical and structural data based on stream sediments, airborne magnetometeric and remote sensing studies. b...

Autonomous robot systems require complex control systems. Fuzzy Logic, a mathematical system developed by Professor Lotfi Zadeh, helps to reduce the complexity of modeling nonlinear problems. In the 1990s, Motorola developed the MC68HC12 microcontroller with native Fuzzy Logic instructions. This research determined the effectiveness of the MC68HC12’s Fuzzy Logic instructions for robotic control...

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...

Fuzzy logic is shown to be a very promising mathematical approach for modelling traffic and transportation processes characterized by subjectivity, ambiguity, uncertainty and imprecision. The basic premises of fuzzy logic systems are presented as well as a detailed analysis of fuzzy logic systems developed to solve various traffic and transportation planning problems. Emphasis is put on the imp...

Abstract— Studies on the effectiveness of fuzzy logic for nonlinear modeling are presented. Although successful applications of fuzzy logic in many diverse areas are reported in the literature, commonly the explicit description of the key features of fuzzy logic yielding these outcomes is not addressed. The present research addresses this issue, to understand the basic features of fuzzy logic i...

In order to tackle high dimensional, complex problems, learning models have go deeper. this article, a novel multilayer ensemble model with first-order evolving fuzzy systems as its building blocks is introduced. The proposed approach can effectively learn from streaming data on sample-by-sample basis and self-organizes multilayered system structure meta-parameters in feedforward, noniterative ...

Despite half a century of fuzzy sets and fuzzy logic progress, as fuzzy sets address complex and uncertain information through the lens of human knowledge and subjectivity, more progress is needed in the semantics of fuzzy sets and in exploring the multi-modal aspect of fuzzy logic due to the different cognitive, emotional and behavioral angles of assessing truth. We lay here the foundations of...

Traditionaly, fuzzy logic has been viewed in the AI community as an approach for managing uncertainty. In the 1990's, however, fuzzy logic has emerged as a paradigm for approximating a functional mapping. This complementary mordern view about the technology offers new insights about the foundation of fuzzy logic as well as new challenges regarding the identification of fuzzy models. In this pap...