The fuzzy virtual object is proposed based on fuzzy modelization of the moving objects in dynamic environments. The fuzzy virtual object is defined as a fuzzy set whose membership function contains the objects’ motion information. It provides a basis of motion control for mobile robots in dynamic environments. A new method of real-time fuzzy robot control is proposed based on the fuzzy environm...

Motivated by the recent successful results of using GIS modeling in a variety of problems related to the geosciences, some knowledge-based methods were applied to a regional scale mapping of the mineral potential, special for Cu-Au mineralization in the Feyz-Abad area located in the NE of Iran. Mineral Prospectivity Mapping (MPM) is a multi-step process that ranks a promising target area for mo...

This paper discusses the issue of how to use fuzzy targets in the targetbased model for decision making under uncertainty. After introducing a target-based interpretation of the expected value on which it is shown that this model implicitly assumes a neutral behavior on attitude about the target, we examine the issue of using fuzzy targets considering different attitudes about the target select...

One of the most recent research areas over the last two decades is the navigation of mobile robots in unknown environments. In this paper, real time navigation for Wheeled Mobile Robot (WMR) using fuzzy logic technique, wireless communication and MATLAB is investigated. Two fuzzy logic controllers (FLCs) with two inputs and two outputs are used to navigate WMR in obstacle ridden environment. Ou...

This paper introduces the idea of viewing fuzzy modelling and fuzzy system design from a functional analysis perspective. Fuzzy transforms, which are based on the generalised Fourier transform in functional analysis, are proposed. It is demonstrated that, mathematically, a T-S fuzzy model is equivalent to a fuzzy transform. Hence the parameters of a T-S fuzzy system can be identified by solving...

The author proposes an extension of genetic algorithm (GA) for solving fuzzy-valued optimization problems. In the proposed GA, values in the genotypes are not real numbers but fuzzy numbers. Evolutionary processes in GA are extended so that GA can handle genotype instances with fuzzy numbers. The proposed method is applied to evolving neural networks with fuzzy weights and biases. Experimental ...

Abstract The priori knowledge of the radar can not be used by the traditional fuzzy C-means clustering algorithm, which leads a poor accuracy of the data association. An improved fuzzy C-means clustering algorithm is proposed in this paper. The real-time change rate of the track slope of moving targets measured by radar is used to update the weight. Then the objective function of fuzzy C-means ...