AIMC Topic: Fuzzy Logic

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On Equivalence of FIS and ELM for Interpretable Rule-Based Knowledge Representation.

IEEE transactions on neural networks and learning systems
This paper presents a fuzzy extreme learning machine (F-ELM) that embeds fuzzy membership functions and rules into the hidden layer of extreme learning machine (ELM). Similar to the concept of ELM that employed the random initialization technique, th...

On fuzzy sampled-data control of chaotic systems via a time-dependent Lyapunov functional approach.

IEEE transactions on cybernetics
In this paper, a novel approach to fuzzy sampled-data control of chaotic systems is presented by using a time-dependent Lyapunov functional. The advantage of the new method is that the Lyapunov functional is continuous at sampling times but not neces...

Alpha-plane based automatic general type-2 fuzzy clustering based on simulated annealing meta-heuristic algorithm for analyzing gene expression data.

Computers in biology and medicine
This paper considers microarray gene expression data clustering using a novel two stage meta-heuristic algorithm based on the concept of α-planes in general type-2 fuzzy sets. The main aim of this research is to present a powerful data clustering app...

Evolutionary fuzzy ARTMAP neural networks for classification of semiconductor defects.

IEEE transactions on neural networks and learning systems
Wafer defect detection using an intelligent system is an approach of quality improvement in semiconductor manufacturing that aims to enhance its process stability, increase production capacity, and improve yields. Occasionally, only few records that ...

Intuitionistic fuzzy interaction bonferroni means and its application to multiple attribute decision making.

IEEE transactions on cybernetics
The Bonferroni mean (BM) was originally presented by Bonferroni and had been generalized by many researchers for its capacity to capture the interrelationship between input arguments. Nevertheless, the existing intuitionistic fuzzy BMs only consider ...

Novel reliable model by integrating the discrete wavelet transform with fuzzy intelligent systems for the simultaneous spectrophotometric determination of anticancer drug and anti-acquired resistance drug in biological samples.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Simultaneous measurement of drugs used to treat cancer and medications prescribed to overcome resistance to these drugs is important in pharmaceutical formulations and biological samples. In this study, a spectrophotometric method with a hybrid of di...

Advancing healthcare innovation with Quality 5.0: a hybrid fuzzy AHP-TOPSIS model for strategic prioritization.

International journal of health care quality assurance
PURPOSE: The present study will outline the systematic approach toward implementing Quality 5.0 in the healthcare industry by focusing on patient-centered innovations. It is concerned with assisting healthcare organizations with digital transformatio...

A novel approach to prioritizing health technology investments using integrated AI-based ranking model.

Journal of health organization and management
PURPOSE: Health technologies are an issue that directly affects the sustainability and quality of health services. Due to budget constraints, it is not financially possible for businesses to apply comprehensive improvement strategies to all these cri...

Kernelized weighted local information based picture fuzzy clustering with multivariate coefficient of variation and modified total Bregman divergence measure for brain MRI image segmentation.

Computers in biology and medicine
This paper proposes a novel clustering method for noisy image segmentation using a kernelized weighted local information approach under the Picture Fuzzy Set (PFS) framework. Existing kernel-based fuzzy clustering methods struggle with noisy environm...

Model-free reinforcement learning control with zero-min barrier functions for constrained systems.

Neural networks : the official journal of the International Neural Network Society
The primary focus of this research is to develop an adaptive output feedback controller designed to minimize a cost-to-go function subject to constraints on input, output, and tracking error for a class of unknown non-affine discrete-time systems. Th...