GWO-FNN: Fuzzy Neural Network Optimized via Grey Wolf Optimization

This study introduces the GWO-FNN model, an improvement of the fuzzy neural network (FNN) architecture that aims to balance high performance with improved interpretability in artificial intelligence (AI) systems. The model leverages the Grey Wolf Optimizer (GWO) to fine-tune the consequents of fuzzy...

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Main Authors: Paulo Vitor de Campos Souza, Iman Sayyadzadeh
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Mathematics
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Online Access:https://www.mdpi.com/2227-7390/13/7/1156
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author Paulo Vitor de Campos Souza
Iman Sayyadzadeh
author_facet Paulo Vitor de Campos Souza
Iman Sayyadzadeh
author_sort Paulo Vitor de Campos Souza
collection DOAJ
description This study introduces the GWO-FNN model, an improvement of the fuzzy neural network (FNN) architecture that aims to balance high performance with improved interpretability in artificial intelligence (AI) systems. The model leverages the Grey Wolf Optimizer (GWO) to fine-tune the consequents of fuzzy rules and uses mutual information (MI) to initialize the weights of the input layer, resulting in greater classification accuracy and model transparency. A distinctive aspect of GWO-FNN is its capacity to transform logical neurons in the hidden layer into comprehensible fuzzy rules, thereby elucidating the reasoning behind its outputs. The model’s performance and interpretability were rigorously evaluated through statistical methods, interpretability benchmarks, and real-world dataset testing. These evaluations demonstrate the model’s strong capability to extract and clearly express intricate patterns within the data. By combining advanced fuzzy rule mechanisms with a comprehensive interpretability framework, GWO-FNN contributes a meaningful advancement to interpretable AI approaches.
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spelling doaj-art-0aed78ebe2284f20878d9ea3b67b4cb72025-08-20T03:06:20ZengMDPI AGMathematics2227-73902025-03-01137115610.3390/math13071156GWO-FNN: Fuzzy Neural Network Optimized via Grey Wolf OptimizationPaulo Vitor de Campos Souza0Iman Sayyadzadeh1Intelligent Digital Agents Research Group, Fondazione Bruno Kessler, 38122 Trento, TN, ItalyRady School of Management, University of California San Diego, La Jolla, CA 92093, USAThis study introduces the GWO-FNN model, an improvement of the fuzzy neural network (FNN) architecture that aims to balance high performance with improved interpretability in artificial intelligence (AI) systems. The model leverages the Grey Wolf Optimizer (GWO) to fine-tune the consequents of fuzzy rules and uses mutual information (MI) to initialize the weights of the input layer, resulting in greater classification accuracy and model transparency. A distinctive aspect of GWO-FNN is its capacity to transform logical neurons in the hidden layer into comprehensible fuzzy rules, thereby elucidating the reasoning behind its outputs. The model’s performance and interpretability were rigorously evaluated through statistical methods, interpretability benchmarks, and real-world dataset testing. These evaluations demonstrate the model’s strong capability to extract and clearly express intricate patterns within the data. By combining advanced fuzzy rule mechanisms with a comprehensive interpretability framework, GWO-FNN contributes a meaningful advancement to interpretable AI approaches.https://www.mdpi.com/2227-7390/13/7/1156AIfuzzy neural networksGWOinterpretability
spellingShingle Paulo Vitor de Campos Souza
Iman Sayyadzadeh
GWO-FNN: Fuzzy Neural Network Optimized via Grey Wolf Optimization
Mathematics
AI
fuzzy neural networks
GWO
interpretability
title GWO-FNN: Fuzzy Neural Network Optimized via Grey Wolf Optimization
title_full GWO-FNN: Fuzzy Neural Network Optimized via Grey Wolf Optimization
title_fullStr GWO-FNN: Fuzzy Neural Network Optimized via Grey Wolf Optimization
title_full_unstemmed GWO-FNN: Fuzzy Neural Network Optimized via Grey Wolf Optimization
title_short GWO-FNN: Fuzzy Neural Network Optimized via Grey Wolf Optimization
title_sort gwo fnn fuzzy neural network optimized via grey wolf optimization
topic AI
fuzzy neural networks
GWO
interpretability
url https://www.mdpi.com/2227-7390/13/7/1156
work_keys_str_mv AT paulovitordecampossouza gwofnnfuzzyneuralnetworkoptimizedviagreywolfoptimization
AT imansayyadzadeh gwofnnfuzzyneuralnetworkoptimizedviagreywolfoptimization