A proposed method for learning rule weights in fuzzy rule-based classification systems

An efficient classifier to diagnose of schizophrenia based on the EEG signals

“…This implies that features of one subject either in the train set or in the test set; hence, there will be no correlation between the train and test features. Fuzzy rule-based classifiers (Zolghadri Jahromi & Taheri, 2008) are another group of well-known classifiers which are suitable for intrusion detection applications (Özyer, Alhajj, & Barker, 2007). This family of classifiers generates a number of If-Then rules randomly that each rule acts as a classifier.…”

Complexity analysis of the biomedical signal using fuzzy entropy measurement

“…Fuzzy logic plays an important role in biomedical signal analysis fields such as pattern recognition, computer vision, machine learning, image analysis, communication, knowledge discovery, and data mining [2,7,[10][11][12]28]. In the study reported in this paper, we formulated another related measure of time series complexity, i.e., fuzzy entropy (FuzzyEn), and applied it to characterize local muscle fatigue electromyography (EMG) signals.…”

Designing a Battlefield Fire Support System Using Adaptive Neuro-Fuzzy Inference System Based Model

“…This combined system has the abilities of deducing knowledge from given rules (which come from the ability of fuzzy inference systems 24 ), learning, generalization, adaptation and parallelism [25][26] (which come from the abilities of ANN). FIS is a framework based on fuzzy set theory and fuzzy if-then rules 27 . The structure of FIS has three main components: a rule base, a database, and a reasoning mechanism …”