Jun 7, 2021 · The problems of fuzzy regression can be solved by using artificial neural networks or evolutionary algorithms (see [49,50,51,52,53,54,55,56,57, ...
Jun 7, 2021 · The problems of fuzzy regression can be solved by using artificial neural networks or evolutionary algorithms (see [49–60]).
A parametric recurrent neural network scheme for solving a class of fuzzy regression models with some real-world applications · Computer Science, Mathematics.
Oct 22, 2024 · In this paper, a hybrid scheme based on recurrent neural networks for approximate coefficients (parameters) of ridge fuzzy regression model ...
Khashei M, Hejazi SR, Bijari M (2008) A new hybrid artificial neural networks and fuzzy regression model for time series forecasting.
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Oct 22, 2024 · Their models consists of solving an optimization problem where the squared difference between observed and estimated spreads of the output is ...
This paper proposes an α-level estimation algorithm for ridge fuzzy regression modeling, addressing the multicollinearity phenomenon in the fuzzy linear ...
Secondly, we propose an algorithm based on fuzzy sets theory which takes advantage of the particular structure of the problem. Two examples are considered for ...
Nov 26, 2020 · The fuzzy regression problems can be solved by applying artificial neural networks and evolutionary algorithms (see [36–45]). For example, ...
An Optimization Technique for Solving a Class of Ridge Fuzzy Regression Problems · A cooperative neural dynamic model for solving general convex nonlinear ...