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Fuzzy Logic

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A combination of deep learning models and type-2 fuzzy for EEG motor imagery classification through spatiotemporal-frequency features.

Journal of medical engineering & technology
Developing a robust and effective technique is crucial for interpreting a user's brainwave signals accurately in the realm of biomedical signal processing. The variability and uncertainty present in EEG patterns over time, compounded by noise, pose n...

Incremental modelling and analysis of biological systems with fuzzy hybrid Petri nets.

Briefings in bioinformatics
Modelling biological systems depends on the availability of data and components of the system at hand. As our understanding of these systems evolves, the ability to gradually refine models by adding new components of different formalisms covering sto...

Interval price prediction of livestock product based on fuzzy mathematics and improved LSTM.

PloS one
Livestock product prices serve as a barometer and bellwether for the agricultural market. However, traditional point prediction techniques focus mainly on tracking or fitting, resulting in limited information and challenges in evaluating the uncertai...

Electroencephalogram (EEG) Based Fuzzy Logic and Spiking Neural Networks (FLSNN) for Advanced Multiple Neurological Disorder Diagnosis.

Brain topography
Neurological disorders are a major global health concern that have a substantial impact on death rates and quality of life. accurately identifying a number of diseases Due to inherent data uncertainties and Electroencephalogram (EEG) pattern overlap,...

Taylor-dingo optimized RP-net for segmentation toward Alzheimer's disease detection and classification using deep learning.

Computational biology and chemistry
Alzheimer's Disease (AD) is a significant cause of mortality in elderly people. The diagnosing and classification of AD using conventional manual operation is a challenging issue. Here, a novel scheme, namely Recurrent Prototypical Network with Taylo...

A fuzzy rank-based deep ensemble methodology for multi-class skin cancer classification.

Scientific reports
Skin cancer is widespread and can be potentially fatal. According to the World Health Organisation (WHO), it has been identified as a leading cause of mortality. It is essential to detect skin cancer early so that effective treatment can be provided ...

Ensemble fuzzy deep learning for brain tumor detection.

Scientific reports
This research presents a novel ensemble fuzzy deep learning approach for brain Magnetic Resonance Imaging (MRI) analysis, aiming to improve the segmentation of brain tissues and abnormalities. The method integrates multiple components, including dive...

Application of machine learning approach to estimate the solubility of some solid drugs in supercritical CO.

Scientific reports
Accurate estimation of the solubility of solid drugs (SDs) in the supercritical carbon dioxide (SC-CO) plays an essential role in the related technologies. In this study, artificial intelligence models (AIMs) by gene expression programming (GEP) and ...

Risk assessment with the fuzzy Fine-Kinney method in a business operating in the metal industry.

International journal of occupational safety and ergonomics : JOSE
Occupational risk assessment involves examining and ranking the risks and hazards in a production or service facility, focusing on workplace health and safety. This study aims to address the deficiencies of traditional methods by applying a fuzzy log...

Fuzzy spatiotemporal event-triggered control for the synchronization of IT2 T-S fuzzy CVRDNNs with mini-batch machine learning supervision.

Neural networks : the official journal of the International Neural Network Society
This paper is centered on the development of a fuzzy memory-based spatiotemporal event-triggered mechanism (FMSETM) for the synchronization of the drive-response interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy complex-valued reaction-diffusion neural...