doi: 10.7763/IJCTE.2011.V3.299
An Improved Prediction Model based on Fuzzy-rough Set Neural Network
Abstract
After the brief review of the basic principles and characteristics of BP (back-propagation) neural network and rough set theory, a novel artificial neural network model based on fuzzy-rough set is proposed in this paper, which is suitable for nonlinear regression to achieve the precise prediction result by introducing improved rough set to obtain minimal attribute set to solve the optimized problem of input layer. Compared to the normal prediction model, the feasibility and effectiveness of the proposed model is verified by a practical case study of the mine gas emission prediction.
Keywords
- fuzzy-rough set
- neural network
- prediction model
How to Cite
Jing Hong, "An Improved Prediction Model based on Fuzzy-rough Set Neural Network," International Journal of Computer Theory and Engineering, vol. 3, no. 1, pp. 158-162, 2011. https://doi.org/10.7763/IJCTE.2011.V3.299
Copyright & License
Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).