Two-string fuzzy inference consists of two separate inference mechanisms: One conventional fuzzy inference system that processes recommending rules, as well as a mechanism for processing negative rules, which prevent the system from outputting their associated values when their premise is fulfilled. Two-string inference has valuable applications in pattern recognition and control tasks. We pres...

This paper deals with center of sum defuzzification method via a computationally attractive method, called transformation function method. A technique for deriving the transformation functions for output fuzzy sets with trapezoidal membership functions has been introduced. It is shown that this method enormously reduces number of mathematical operations and amount of memory space required to co...

In this paper, we present a new method for fuzzy risk analysis based on ranking generalized fuzzy numbers with different heights and different spreads. First, we present a new method for ranking generalized fuzzy numbers. The proposed method considers the defuzzified values, the heights and the spreads for ranking generalized fuzzy numbers. Based on the proposed method for ranking generalized f...

Fuzzy Hamming Distance is successfully used in a Content-Based Image Retrieval (CBIR) system as a similarity measure. The system performs a m × n partitioning of the compared images and for each partitions pairs evaluates FHD. In the last step the FHD are defuzzified and the results are combined in a final score. In order to take full advantage of the use of fuzzy sets, the current study invest...

Type-2 defuzzification is a two-stage process. Type-reduction, the first stage, gives rise to a type-1 fuzzy set known as the type-reduced set (TRS), which for the second stage is defuzzified to give a crisp number. This paper focusses on the TRS itself, which reveals a fascinating internal structure. We provide a description of and explanation for this structure, then go on to suggest how it m...

This paper will present a novel method based on harmonic mean, geometric mean, arithmetic mean and root mean square to help reduce fuzzy rules. The objective of the new method proposed is to produce fuzzy models with both a small number of interpretable rules and sufficiently high precision. Comparisons will be made between systems utilizing reduced rules and original rules to verify efficacy o...

Defuzzification of type-2 fuzzy sets is a computationally intense problem. This paper proposes a new approach for defuzzification of interval type-2 fuzzy sets. The collapsing method converts an interval type-2 fuzzy set into a representative embedded set (RES) which, being a type-1 set, can then be defuzzified straightforwardly. The novel Representative Embedded Set Theorem (REST), with which ...

The purpose of this paper is to study fully fuzzy multi-choice multiobjective linear programming problem (FFMMOLPP), in which, right hand side of each constraint has two choices. With the help of ranking function, deviation distance and deviation degree between two fuzzy numbers are defined. A new method is proposed to find the  fuzzy pareto optimal solution of FFMMOLPP which is defuzzified by...

This model presents the invention scheduling difficulty in industry with different operational constraints, as well as strategic plan of the business, revenue purpose, and limit on finishing. In this article, we have studied an inventory model for deteriorating items with shortages under partially backlogging. The aim of present study is to minimize the total cost function in fuzzy environment....

Obesity has been linked to several heart diseases .Unfortunately, Malaysian today are the most overweight or obese people among Asian nations. That is, half of population is overweight. These serious social consequences. Therefore, specific and actions needed reduce eliminate this threat. The rapid increase in obesity rates directed link with factors such as low physical activities, ease transp...