sustainable development is very important especially in environment. in this paper, the value of sustainable development in environment of iran for iron and steel making in comparison with global, determined by fuzzy logic and expressed by continuous value between zero and one. the following steps were taken in turn: 1- obtaining the related data from internal resources. 2- defining membership ...

In this paper a novel handoff decision algorithm for the mobile subsystem of tactical communications systems is introduced. In this algorithm, handoff decision metrics are: received signal strength measurements from the access points, the ratio of the used capacity to the total capacity for the access points, and relative directions and speeds of the mobiles to the access points. We use a fuzzy...

In neuro-fuzzy approaches different membership functions are used for modeling the system's rule set. Two wellknown membership function types are triangle functions and trapezoid functions. In our contribution we demonstrate that trapezoid functions with larger core regions are the more appropriate functions for calculating the membership degrees within neuro-fuzzy systems. If regions of the da...

There has been some debate about the correspondence between typicality gradients and category membership. The present study investigates the relationship between these two measures in the domains of animals and artifacts. Forty-two adults judged the degree of typicality or category membership of 293 animals and artifacts. The subjects' tendency for animals, but not for artifacts, was to make mo...

A simple probabilistic grounding of the ”fuzzy set membership degree” is presented, and used to provide definitions of the absolute and conditional probabilities of fuzzy sets. Among other possible applications, this allows fuzzy membership values to be coherently incorporated into probabilistic reasoning processes.

This paper proposes a web-based laboratory resource supply chain conceptual model for an educational institution to increase the process and information integration, visibility and flexibility. The proposed model utilizes a reasoning engine with fuzzy, parallel fuzzy rules, and de-fuzzy processes to decide the optimal purchase ordering quantity and the best constant stocks in the laboratory. Th...

The choice of membership functions plays an essential role in the success of fuzzy systems. This is a complex problem due to the possible lack of knowledge when assigning punctual values as membership degrees. To face this handicap, we propose a methodology called Ignorance functions based Interval-Valued Fuzzy Decision Tree with genetic tuning, IIVFDT for short, which allows to improve the per...

This chapter demonstrates how a neuro-fuzzy approach could produce outputs of a further-modified multi-criteria decision-making (MCDM) quality function deployment (QFD) model within the required error rate. The improved fuzzified MCDM model uses the modified S-curve membership function (MF) as stated in an earlier chapter. The smooth and flexible logistic membership function (MF) finds out fuzz...

This paper proposes a new method of feature extraction and recognition, namely, the fuzzy inverse Fisher discriminant analysis (FIFDA) based on the inverse Fisher discriminant criterion and fuzzy set theory. In the proposed method, a membership degree matrix is calculated using FKNN, then the membership degree is incorporated into the definition of the between-class scatter matrix and withinExp...

k-nearest neighbors (k-NN), which is known to be a simple and efficient approach, is a non-parametric supervised classifier. It aims to determine the class label of an unknown sample by its k-nearest neighbors that are stored in a training set. The k-nearest neighbors are determined based on some distance functions. Although k-NN produces successful results, there have been some extensions for ...