Fusion of Computational Intelligence Techniques and Their Practical Applications

Abiyev, Rahib H.; Aliev, R. A.; Kaynak, Okyay; Türkşen, I.B.; Bonfig, Karl Walter

doi:10.1155/2015/463147

Cited by 6 publications

(2 citation statements)

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“…ANNs, evolutionary computation, swarm intelligence, artificial immune systems, and fuzzy logic are some of the AI paradigms which have been used effectively to solve real-life problems (Abiyev et al, 2015;Engelbrecht, 2007;Jain and De Wilde, 2012;Zhu, 2014). Each of these paradigms originates from biological systems, has biological motivation and models biological and natural intelligence.…”

Section: Learning Theoriesmentioning

confidence: 99%

Artificial Neural Network and Its Applications in the Energy Sector – An Overview

Babatunde

Anozie

Omoleye

2020

IJEEP

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In order to realize the goal of optimal use of energy sources and cleaner environment at a minimal cost, researchers; field professionals; and industrialists have identified the expediency of harnessing the computational benefits provided by artificial intelligence (AI) techniques. This article provides an overview of AI, chronological blueprints of the emergence of artificial neural networks (ANNs) and some of its applications in the energy sector. This short survey reveals that despite the initial hiccups at the developmental stages of ANNs, ANN has tremendously evolved, is still evolving and have been found to be effective in handling highly complex problems even in the areas of modeling, control, and optimization, to mention a few.

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Section: Learning Theoriesmentioning

confidence: 99%

Artificial Neural Network and Its Applications in the Energy Sector – An Overview

Babatunde

Anozie

Omoleye

2020

IJEEP

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“…As mentioned above, recently a number of different approaches have been used for designing fuzzy if-then rules. Some of them are based on clustering [ 20 – 24 , 26 ], the least squares method (LSM) [ 20 , 22 , 30 ], gradient algorithms [ 14 , 20 – 23 , 26 ], genetic algorithms [ 24 , 25 , 28 ], and particle swarm optimization (PSO) [ 31 ].…”

Section: Parameter Updatesmentioning

confidence: 99%

Diagnosing Parkinson’s Diseases Using Fuzzy Neural System

Abiyev

Abizade

2016

Computational and Mathematical Methods in Medicine

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This study presents the design of the recognition system that will discriminate between healthy people and people with Parkinson's disease. A diagnosing of Parkinson's diseases is performed using fusion of the fuzzy system and neural networks. The structure and learning algorithms of the proposed fuzzy neural system (FNS) are presented. The approach described in this paper allows enhancing the capability of the designed system and efficiently distinguishing healthy individuals. It was proved through simulation of the system that has been performed using data obtained from UCI machine learning repository. A comparative study was carried out and the simulation results demonstrated that the proposed fuzzy neural system improves the recognition rate of the designed system.

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Fuzzy Logic Approach in the Social Sciences

García-Pardo,

Bárcena-Martín

2023

Encyclopedia of Quality of Life and Well-Being Research

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Fusion of Computational Intelligence Techniques and Their Practical Applications

Cited by 6 publications

References 1 publication

Artificial Neural Network and Its Applications in the Energy Sector – An Overview

Artificial Neural Network and Its Applications in the Energy Sector – An Overview

Diagnosing Parkinson’s Diseases Using Fuzzy Neural System

Fuzzy Logic Approach in the Social Sciences

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