A common algorithm to solve the shortest path problem (SPP) is the Dijkstra algorithm. In this paper, a generalized Dijkstra algorithm is proposed to handle SPP in an uncertain environment. Two key issues need to be addressed in SPP with fuzzy parameters. One is how to determine the addition of two edges. The other is how to compare the distance between two different paths with vailable online ...

In this paper the fault detection problem is solved using an alternative methodology based on a fuzzy/Bayesian strategy combining a Bayesian network and the fuzzy set theory. The new important issue in this proposed methodology is to address uncertainties in the input of the Bayesian Network. This contribution is possible since the fuzzy set theory is used as the knowledge representation. To il...

The present paper describes the development of an indirect adaptive fuzzy control scheme employing feedback linearizing technique. The scheme proposes the development of a fuzzy certainty equivalence controller for controlling non-linear plants. This controller is designed on the basis of plant parameccepted 3 January 2011 vailable online 11 January 2011 eywords: ndirect adaptive control ters e...

A type-2 Takagi-Sugeno-Kang fuzzy neural system is proposed and its parameter update rules are derived using fuzzy clustering and gradient learning algorithms. The proposed type-2 fuzzy neural system is used for the control and the identification of a real-time servo system. Fuzzy c-means clustering algorithm is used to determine the initial places of the membership functions to ensure that the...

uzzy logic is a powerful way to put engineering expertise into products in a short amount of time. It’s highly beneficial in automotive engineering, where many system designs involve the experience of design engineers as well as test drivers. Over the past years, fuzzy logic has become is a common design technology in Japan, Korea, Germany, Sweden, and France. The reasons are manifold. First, c...

Tumor classification based on gene expression levels is important for tumor diagnosis. Since tumor data in gene expression contain thousands of attributes, attribute selection for tumor data in gene expression becomes a key point for tumor classification. Inspired by the concept of gain ratio in decision tree theory, an attribute selection method based on fuzzy gain ratio under the framework of...

In this paper, optimal control for stochastic linear quadratic singular neuro Takagi–Sugeno (T-S) fuzzy system with singular cost is obtained using genetic programming(GP). To obtain the optimal control, the solution of matrix Riccati differential equation (MRDE) is computed by solving differential algebraic equation (DAE) using a novel and nontraditional GP approach. The obtained solution in t...

A bst ract : Based on the T-S model ,the output regulation of nonlinear singularly perturbed systems via state feedback is dis2 cussed. It is shown that , under standard assumptions ,this problem is solvable if and only if certain linear matrix equations are solv2 able. Once these equations are solvable , the state feedback regulator can easily be constructed. Keywor ds : Nonlinear systems ; Ou...