this paper develops an automatic parking algorithm based on a fuzzy logic controller with the vehicle pose for the input and the steering angle for the output. in this way some feasible reference trajectory path have been introduced according to geometric and kinematic constraints and nonholonomic constraints to simulate motion path of car. also a novel method is used for parking space detectio...

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...

This paper is focused on the evolution of the theory of fuzzy IF-THEN rules and its contribution to the establishment of fuzzy logic. I advocate that Hájek’s fuzzy logic is a right methodology for development of special logical theories. A theory of fuzzy IF-THEN rules (as a special theory in this sense) is proposed. This theory is for all practitioners who want to create a system of fuzzy IF-T...

Fuzzy inference systems and neural networks are complementary technologies in the design of adaptive intelligent systems. Artificial Neural Network (ANN) learns from scratch by adjusting the interconnections between layers. Fuzzy Inference System (FIS) is a popular computing framework based on the concept of fuzzy set theory, fuzzy if-then rules, and fuzzy reasoning. A neuro-fuzzy system is sim...

In this paper, the fuzzy multi-depot vehicle routing problem with simultaneous pickup and delivery (FMDVRP-SPD) is investigated. The FMDVRP-SPD is the problem of allocating customers to several depots, so that the optimal set of routes is determined simultaneously to serve the pickup and the delivery demands of each customer within scattered depots. In the problem, both pickup and delivery dema...

In this paper we show that some applications of a fuzzy methodology in medical diagnosis were ”inspired” by probabilistic approaches. Although probability theory and fuzzy set theory describe different facets of uncertainty. In this paper we trace the transformation of statistical measures of diagnostic accuracy to fuzzy occurrence, exclusion and confirmation relations, applied in several fuzzy...

in this paper, a numerical method for nding minimal solution of a mn fullyfuzzy linear system of the form ax = b based on pseudo inverse calculation,is given when the central matrix of coecients is row full rank or column fullrank, and where a~ is a non-negative fuzzy mn matrix, the unknown vectorx is a vector consisting of n non-negative fuzzy numbers and the constant b isa vector consisti...

background and objectives: evaluating the performance of clinical units is critical for effective managementof health settings. certain assessment of clinical variables for performance analysis is not always possible,calling for use of uncertainty theory. this study aimed to develop and evaluate an integrated independentcomponent analysis-fuzzy-data envelopment analysis approach to accurate the...

in this paper, the problem of determining the quality level, lead time for order delivery and price of a product produced by a manufacturer is considered. in this problem the demand for the product is influenced by all three decision variables: price, lead time and quality level. to formulate the demand function, a fuzzy rule base that estimates the demand value based on the three decision vari...

In this thesis, an intelligent fuzzy logic system using genetic algorithms for the prediction and modelling of interest rates is developed. The proposed system uses a Hierarchical Fuzzy Logic system in which a genetic algorithm is used as a training method for learning the fuzzy rules knowledge bases. A fuzzy logic system is developed to model and predict three month quarterly interest rate flu...