This paper focuses on the data-driven generation of fuzzy IF...THEN rules. The resulted fuzzy rule base can be applied to build a classifier, a model used for prediction, or it can be applied to form a decision support system. Among the wide range of possible approaches, the decision tree and the association rule based algorithms are overviewed, and two new approaches are presented based on the...

Estimating the depth of anesthesia (DOA) is still a challenging area in anesthesia research. The objective of this study was to design a fuzzy rule based system which integrates electroencephalogram (EEG) features to quantitatively estimate the DOA. The proposed method is based on the analysis of single-channel EEG using frequency and time domain methods. A clinical study was conducted on 22 pa...

Conventional fuzzy logic controllers (FLC) are frequently being used to wherever the load is non-linear or when the mathematical model of a plant is unknown or to make a system or plant robust to external disturbances. The main working of the fuzzy logic controller depends upon the number of rules present in the rule base. Higher the number of rules better is the performance. However, with the ...

This paper uses a methodology based in Fuzzy Sets Theory in order to describe the interaction between the prey, Aphis glycines (Hemiptera: Aphididae)—the soybean aphid, and its predator, Orius insidiosus (Hemiptera: Anthocoridae) and to propose a biological control to soybean aphid. Economic thresholds were already developed for this pest. The model includes biotic (predator) and abiotic (tempe...

In this paper, fuzzy economic order quantity (EOQ) model for inventory system with partial backorder is proposed. The fuzzy total relevance cost of the model is calculated under function principle. The optimal EOQ is derived using median rule. Fuzzy variables are appropriate when the exact information is unavailable. In the proposed model, the optimal solution for the fuzzy EOQ model is higher ...

Adaptive genetic algorithms dynamically adjust the genetic algorithm connguration during the course of evolving a problem solution in order to ooer an appropriate balance between exploration (overall search in the solution space) and exploitation (localized search in the promising regions discovered in that space). One promising way followed for building adaptive genetic algorithms involves the...

We propose in this paper to model of a rule based expert systems using the techniques of Fuzzy sets and Fuzzy logic. In the real world problem solving is the process of finding a solution when the path leading to that solution is uncertain. The Expert Systems need to have the ability to handle vague associations, for example by accepting the degree of correlations as numerical certainty factors...

This contribution is concerned with the interpretability of fuzzy rule-based systems. While this property is widely considered to be a crucial one in fuzzy rule-based modeling, a more detailed formal investigation of what "interpretability" actually means is not available. So far, interpretability has most often been associated with rather heuristic assumptions about shape and mutual overlappin...

Fuzzy rule interpolation forms an important approach for performing inference with systems comprising sparse rule bases. Even when a given observation has no overlap with the antecedent values of any existing rules, fuzzy rule interpolation may still derive a useful conclusion. Unfortunately, very little of the existing work on fuzzy rule interpolation can conjunctively handle more than one for...