We consider function approximation by fuzzy systems. Fuzzy systems are typically used for approximating deterministic functions, in which the stochastic uncertainty is ignored. We propose probabilistic fuzzy systems in which the probabilistic nature of uncertainty is taken into account. Furthermore, these systems take also fuzzy uncertainty into account by their fuzzy partitioning of input and ...

This paper presents an approach to analyze the thematic evolution of a given research field. This approach combines performance analysis and sciencemapping for detecting and visualizing conceptual subdomains (particular themes or general thematic areas). It allows us to quantify and visualize the thematic evolution of a given research field. To do this, coword analysis is used in a longitudinal...

This paper reports the evaluation of Fuzzy logic implemented on image, in MATLAB environment, used to implement different functions. In this paper, the in-built functions of MATLAB are implemented on image and the resultant images are displayed using different functions. Fuzzy inference system has been designed for four inputs, one output that tells whether the pixel under consideration is “low...

To tackle the problem with inexact, uncertainty and vague knowl- edge, constructive method is utilized to formulate lower and upper approx- imation sets. Rough set model over dual-universes in fuzzy approximation space is constructed. In this paper, we introduce the concept of rough set over dual-universes in fuzzy approximation space by means of cut set. Then, we discuss properties of rough se...

Grey systems and interval valued fuzzy sets appear to be similar concepts. This abstract provides a brief introduction to grey systems and compares them to interval valued fuzzy sets. We argue that grey system is similar to an interval fuzzy set, but has different properties. Grey systems focus on the interval range of the system property itself, but interval fuzzy sets consider the fuzzy membe...

  Selection of appropriate infrastructure transportation projects such as highways, plays an important role in promotion of transportation systems. Usually in evaluation of transportation projects, because of lack of information or due to long time and high expenditures needed for gathering information, different effective factors are ignored. Thus, in this research, regarding multi criteria na...

expert systems can help to build banks customers' credit scoring models. here, selection of key features of the credit scoring is important. also, it is possible to express the features values as fuzzy. the problem is how to improve features selection by genetic algorithm, in way that these features can be employed as input in fuzzy expert system. this paper presents a hybrid credit scorin...

Instead of describing a fuzzy modeling algorithm that is new, powerful, robust, and with outstanding learning abilities, the objective of this paper is to point out four important topics usually “ignored” in fuzzy model’s design. These are: 1. The generalization ability of the fuzzy model. 2. The appearance of empty rules at a fuzzy model whose conclusions could not be extracted. 3. The presenc...

Different generalizations to the case of coverings of the standard approach to entropy applied to partitions of a finite universe X are explored. In the first approach any covering is represented by an identity resolution of fuzzy sets on X and a corresponding probability distribution with associated entropy is defined. A second approach is based on a probability distribution generated by the c...

Spatial decision making is a fundamental function of contemporary Geographic Information Systems (GIS). One of the most fertile GIS development areas is integrating multiple criteria decision models (MCDM) into GIS querying mechanisms. The classic approach for this integration has been to use Boolean techniques of MCDM with crisp representations of spatial objects (features) to produce static m...