Multilayer Perceptron for Robust Nonlinear Interval Regression Analysis Using Genetic Algorithms
On the basis of fuzzy regression, computational models in intelligence such as neural networks have the capability to be applied to nonlinear interval regression analysis for dealing with uncertain and imprecise data. When training data are not contaminated by outliers, computational models perform...
Saved in:
Main Author: | Yi-Chung Hu |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2014-01-01
|
Series: | The Scientific World Journal |
Online Access: | http://dx.doi.org/10.1155/2014/970931 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Data Imputation for Detected Traffic Volume of Freeway Using Regression of Multilayer Perceptron
by: Xiang Wang, et al.
Published: (2022-01-01) -
Integrating Multilayer Perceptron and Support Vector Regression for Enhanced State of Health Estimation in Lithium-Ion Batteries
by: Sadiqa Jafari, et al.
Published: (2025-01-01) -
Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics
by: F. Cadini, et al.
Published: (2008-01-01) -
Passenger Flow Scale Prediction of Urban Rail Transit Stations Based on Multilayer Perceptron (MLP)
by: Luzhou Lin, et al.
Published: (2023-01-01) -
An Improved Directed Crossover Genetic Algorithm Based on Multilayer Mutation
by: Feng Xie, et al.
Published: (2022-01-01)