In interval type-2 fuzzy logic controllers (IT2-FLCs), the output processing includes type reduction and defuzzification. Recently, researchers have proposed many efficient type reduction algorithms, but there are no effective schemes to improve the output of defuzzification. This paper presents a geneticalgorithm-based type reduction algorithm, which reduces the type of an interval type-2 fuzz...

The application of fuzzy time series models to forecasting has been drawing a great amount of attention. To provide a more sophisticated model to handle real world problems thus becomes important. This study intends to model fuzzy time series with multiple observations at a single time point. The proposed model shows how to fuzzify multiple observations into a fuzzy set. Neural networks are app...

This paper analysis single-period inventory models with discrete demand under fuzzy environment. In the proposed models three different cases are examined. In the first case, demand is represented by a triangular fuzzy number and a discrete membership function. In the second case, demand is a stochastic variable while inventory costs such as unit holding cost and unit shortage cost are imprecis...

We examine a linear programming problem formulation in which the constraint coefficients are not precisely given in the work. We investigate the possibility of applying GAs to solve this kind of fuzzy linear programming problem without defining membership functions for fuzzy numbers, using the extension principle, interval arithmetic, and α-cut operations for fuzzy computations, and using a pen...

In this paper we show how combining fuzzy sets and reinforcement learning a winning agent can be created for the popular Pac-man game. Key elements are the classification of the state into a few fuzzy classes that makes the problem manageable. Pac-man policy is defined in terms of fuzzy actions that are defuzzified to produce the actual Pac-man move. A few heuristics allow making the Pac-man st...

This paper proposes a rule base compression method for fuzzy systems. The method is based on filtration of rules with identical linguistic values for the output that are known as non-monotonic rules. The filtration removes the redundant computations in the fuzzy inference with respect to the crisp values of the inputs to the fuzzy system. The method identifies the redundant rules after fuzzific...

-A revolutionary innovation in the field of navigation aids, help pilots to have a smooth and safe landing. Landing depends upon the two factors: elevator deflection and throttle deflection; the relation between the two should be maintained in order to acquire a non-oscillatory output response. Membership function are developed using the crisp values of velocity and height of an aircraft. Fuzzi...

The present work describes a new approach to integrating structural knowledge into the image classification process. First, a fuzzy classifier produces a fuzzy partition of the image. Then, the defuzzified (crisp) partition is tried to be improved. According to the membership degrees in the fuzzy partition, the system selects a set of pixels and associates a set of candidate classes with each o...

It is the purpose of this paper to investigate the integrated cost minimizing strategy with supplier’s trade credits offer under fuzzy environment. Supplier permits the retailer a certain fixed period to settle the amount owed to him for the items supplied. Expressions for average integrated inventory cost in fuzzy sense are derived Signed Distance Method is used to defuzzified total fuzzy cost...