Current Trends and Challenges in Applying Metaheuristics to the Innovative Area of Weight and Structure Determination Neuronets

The weights and structure determination (WASD) neuronet (or neural network) is a single-hidden-layer feedforward neuronet that exhibits an excellent approximation ability, despite its simple structure. Thanks to its strong generalization, fast speed, and ease of implementation, the WASD neuronet has...

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Published inInventions (Basel) Vol. 10; no. 4; p. 62
Main Authors Mourtas, Spyridon D., Li, Shuai, Cao, Xinwei, Liao, Bolin, Katsikis, Vasilios N.
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.08.2025
Subjects
Algorithms
Approximation
Artificial intelligence
Classification
Cognitive tasks
Forecasts and trends
Heuristic methods
Machine learning
Moore–Penrose inverse
Neural networks
Neurons
Polynomials
Real time
single-hidden-layer feedforward neuronet
Trends
weights and structure determination
United States
New Jersey
Germany
Online AccessGet full text
ISSN2411-5134
2411-5134
DOI10.3390/inventions10040062

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Abstract The weights and structure determination (WASD) neuronet (or neural network) is a single-hidden-layer feedforward neuronet that exhibits an excellent approximation ability, despite its simple structure. Thanks to its strong generalization, fast speed, and ease of implementation, the WASD neuronet has been the subject of many modifications, including metaheuristics, and applications in a wide range of scientific fields. As it has garnered significant attention in the last decade, the aim of this study is to provide an extensive overview of the WASD framework. Furthermore, the WASD has been effectively used in numerous real-time learning tasks like regression, multiclass classification, and binary classification due to its exceptional performance. In addition, we present WASD’s applications in social science, business, engineering, economics, and medicine. We aim to report these developments and provide some avenues for further research.
AbstractList The weights and structure determination (WASD) neuronet (or neural network) is a single-hidden-layer feedforward neuronet that exhibits an excellent approximation ability, despite its simple structure. Thanks to its strong generalization, fast speed, and ease of implementation, the WASD neuronet has been the subject of many modifications, including metaheuristics, and applications in a wide range of scientific fields. As it has garnered significant attention in the last decade, the aim of this study is to provide an extensive overview of the WASD framework. Furthermore, the WASD has been effectively used in numerous real-time learning tasks like regression, multiclass classification, and binary classification due to its exceptional performance. In addition, we present WASD’s applications in social science, business, engineering, economics, and medicine. We aim to report these developments and provide some avenues for further research.
Audience Academic
Author Cao, Xinwei
Mourtas, Spyridon D.
Li, Shuai
Katsikis, Vasilios N.
Liao, Bolin
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Snippet The weights and structure determination (WASD) neuronet (or neural network) is a single-hidden-layer feedforward neuronet that exhibits an excellent...
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SubjectTerms Algorithms
Approximation
Artificial intelligence
Classification
Cognitive tasks
Forecasts and trends
Heuristic methods
Machine learning
Moore–Penrose inverse
Neural networks
Neurons
Polynomials
Real time
single-hidden-layer feedforward neuronet
Trends
weights and structure determination
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Title Current Trends and Challenges in Applying Metaheuristics to the Innovative Area of Weight and Structure Determination Neuronets
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