Data-driven fuzzy modeling has been used in a wide variety of applications. However, in fuzzy rule-based models acquired from numerical data, redundancy often exists in the form of redundant rules or similar fuzzy sets. This results in unnecessary structural complexity and decreases the interpretability of the system. In this paper, a rule-base self-extraction and simpli&cation method is propos...

-Based on the fuzzy set theory, this study introduces three novel three-phase fuzzy feeder models for fast distribution system calculations. These fuzzy models are formulated using three lumped individual phase loads to represent single-phase, three-phase unbalanced, and nonuniformly distributed loads along a feeder. The proposed voltage-drop and line-loss fuzzy models are developed to accurate...

Fuzzy models have been designed to represent approximate or imprecise relationships in complex systems and have been successfully employed in control systems, expert systems, and decision analysis. Classically, fuzzy models were built from human expertise and knowledge of the system being modeled. As systems have grown more complex it has become increasingly difficult to construct models direct...

Concepts of graph theory have applications in many areas of computer science including data mining, image segmentation, clustering, image capturing, networks, etc . An interval-valued fuzzy set is a generalization of the notion of a fuzzy set. Interval-valued fuzzy models give more precision, flexibility and compatibility to the system as compared to the fuzzy models. In this paper, we introduc...

In this paper, single and multi container maintenance model under limited time interval of interest is introduced in fuzzy environment. These fuzzy models are solved by fuzzy geometric programming technique. Here fuzzy geometric programming is discussed through fuzzy decision-making processes with three different operators, max-min, max-average mean, and max-geometric mean. These operators are ...