Fuzzy Neural Networks based on Fuzzy Logic Neurons Regularized by Resampling Techniques and Regularization Theory for Regression Problems

Fuzzy Neural Networks based on Fuzzy Logic Neurons Regularized by Resampling Techniques and Regularization Theory for Regression Problems

This paper presents a novel learning algorithm for fuzzy logic neuron based on neural networks and fuzzy systems able to generate accurate and transparent models. The learning algorithm is based on ideas from Extreme Learning Machine [36], to achieve a low time complexity, and regularization theory...

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Bibliographic Details
Main Authors: Paulo Vitor de Campos Souza, Augusto Junio Guimaraes, Vanessa Souza Araújo, Thiago Silva Rezende, Vinicius Jonathan Silva Araújo
Format: Article
Language:English
Published: Asociación Española para la Inteligencia Artificial 2018-11-01
Series:Inteligencia Artificial
Subjects:
Bootstrap lasso
Extreme Learning Machines
Regression Problems
Fuzzy Neural Network
Fuzzy Logic Neurons
Online Access:https://journal.iberamia.org/index.php/intartif/article/view/169

Internet

https://journal.iberamia.org/index.php/intartif/article/view/169

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