AIMC Topic: Fuzzy Logic

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Flemboda artificial intelligence: hybrid fuzzy-convolutional neural network for efficient chromosome abnormality classification.

Molecular genetics and genomics : MGG
Chromosomal abnormality detection is a fundamental task in clinical genetics, as accurate identification of structural and numerical defects is essential for reliable diagnosis and treatment planning. However, many existing learning-based approaches ...

Virtual parking path planning in narrow roads based on fuzzy pure pursuit algorithm.

PloS one
To address the issues of low adaptability and significant tracking errors in parking scenarios when using fixed look-ahead distance Pure Pursuit (PP) algorithms, this paper proposes an automatic parking path tracking control algorithm based on Fuzzy ...

An intuitionistic fuzzy automated negotiation model for personalized and efficient shared decision-making.

Scientific reports
Shared decision-making (SDM) is a healthcare decision-making model that integrates patient preferences with medical expertise. It seeks to foster active involvement, enhance satisfaction, and strengthen the doctor-patient relationship. However, SDM a...

A novel algorithm for model uncertainty reduction in trapezoidal fuzzy fault tree risk assessment.

PloS one
Intelligent risk assessment in complex systems increasingly relies on methods like trapezoidal fuzzy fault trees. However, conventional techniques often struggle with accurately calculating top-event probabilities and handling model uncertainty, whic...

Applications of newly defined diamond Pythagorean fuzzy CODAS method via multi-criteria decision-making problems.

PloS one
The diverse decision values may fail to capture an accurate perspective when multiple decision-makers are part of the process. To address this challenge, this work introduces the diamond Pythagorean fuzzy set (Dia‑PyFS), an advancement over both the ...

Robust missing data reconstruction in schizophrenia using tracking-removed autoencoder with fuzzy confidence integration.

Scientific reports
Neural network models for outcome prediction play a pivotal role in neurological disease research, particularly for baseline risk assessment. Schizophrenia, a complex and relatively rare neuropsychiatric disorder, presents significant diagnostic chal...

EEG based epileptic seizure detection using SVM fuzzy learning and metaheuristic optimization.

Scientific reports
The brain condition known as epilepsy has an impact on patients' quality of life. The need for computer-automated diagnosis systems (CADS) has arisen due to the shortcomings of conventional clinical and machine learning techniques as well as the shor...

Enhancing museum collection images with fuzzy set guided convolutional neural network: A novel approach leveraging fuzzy set theory.

PloS one
Museum collection images are invaluable for preserving cultural heritage and studying history. However, these images often lack quality and clarity. This study introduces a novel museum collection image enhancement technique based on fuzzy set theory...

Deep Fuzzy-NN modeling for the prediction of Zn(II) adsorption in columns using alkaline modified biochar: Integrated experimental and computational insights.

Environmental research
The precise prediction of adsorption process is significant in the optimization of pollutant removal systems. In this research, deep fuzzy neural network (DFNN) model was developed for the prediction of Zn(II) removal efficiency using alkaline activa...

Fuzzy guided ensemble inference system for brain tumor classification.

Brain research
The abnormal growth of cells inside or near the brain is called a brain tumor. Brain tumors can be benign (non-cancerous) or malignant (cancerous). Both these types can exert pressure on the surrounding brain tissue, increasing intracranial pressure....