UPSO-FSVRNET: Fuzzy Identification Approach in a VANET Environment Based on Fuzzy Support Vector Regression and Unified Particle Swarm Optimization

Sellami, Lamaa; Alaya, Bechir

doi:10.1007/s40815-022-01408-7

Cited by 1 publication

(1 citation statement)

References 41 publications

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“…In addition, fuzzy logic is a mathematical function that uses fuzzy rules to convert input data to a scalar value. Concurrently, numerous outputs are viewed as a distinct multi-input set or a technique of multiple logic derived from fuzzy set theory frequently applied when a similar conclusion suffices [13].…”

Section: Fuzzy Logic Systemsmentioning

confidence: 99%

Python scikit-fuzzy: developing a fuzzy expert system for diabetes diagnosis

Rosli Razak,

Zia Ul-Saufie,

Yusoff

et al. 2024

IJ-AI

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Nowadays, improvements in diabetes detection that provide patients with vital information are needed. This is due to the fact that Diabetes mellitus has generated a worldwide epidemic that costs society and people. Also, patients tend to misread symptoms, and clinicians who collect insufficient data may produce erroneous outcomes. Therefore, this study aims to demonstrate that a programme that integrates expert advice such as decisions, recommendations, or solutions is an excellent method for reducing the incidence of diabetes. Specifically, this study intends to implement a fuzzy expert system that can detect and report the early stages of diabetes as a viable approach. Furthermore, since this programme is available to everyone, people may easily self-diagnose themselves if they have a blood glucose monitoring device. However, developing the fuzzy expert system for real-world situations, such as diabetes patients, using any programming tools is not straightforward. Therefore, this study will provide a comprehensive approach to constructing a fuzzy expert system using the popular programming language Python.

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Section: Fuzzy Logic Systemsmentioning

confidence: 99%