Rule generation in complex data analysis tasks poses challenges in terms of accuracy and
interpretability. This research proposes a novel approach called Quantum-Inspired Fuzzy …

The superior performance of quantum computers in some problems lies in the direct use of
quantum mechanics phenomena. This ability has originated the quantum-inspired …

This article is concerned with the development of fuzzy models realized with the aid of
genetic programming (GP). The proposed architecture employs GP to form fuzzy logic …

The performance of the neural network (NN) depends on the various parameters such as
structure, initial weight, number of hidden layer neurons, and learning rate. The …

Nowadays fuzzy logic is increasingly used in decision-aided systems since it offers several
advantages over other traditional decision-making techniques. The fuzzy decision support …

One of the goals of financial institutions is to reduce credit risk. Consequently they must
properly select customers. There are a variety of methodologies for credit scoring, which …

This paper presents the results of the implementaion of a combination of a real-coded and
binary-like coded genetic algorithm (RBLGA) to automatically generate fuzzy knowledge …

The use of fuzzy quantifiers to modify the fuzzy linguistic terms in fuzzy models helps build
fuzzy systems in a more natural way, by capturing finer pieces of information embedded in …

We propose the Quantum-Inspired Multi-Gene Lin-ear Genetic Programming (QIMuLGP),
which is a generalization of Quantum-Inspired Linear Genetic Programming (QILGP) model …

This work focus on the genetic generation of fuzzy systems. One of the main contribution of
this work is the proposal of the FCA-BASED method, which generates the genetic search …