Genetic algorithm based adaptive neural network ensemble and its application in predicting carbon flux
By: Y. Xue, S. Liu, Y. Hu, J. Yang, and Q. Chen
Links
- More information: Publisher Index Page (via DOI)
- Download citation as: RIS | Dublin Core
Abstract
To improve the accuracy in prediction, Genetic Algorithm based Adaptive Neural Network Ensemble (GA-ANNE) is presented. Intersections are allowed between different training sets based on the fuzzy clustering analysis, which ensures the diversity as well as the accuracy of individual Neural Networks (NNs). Moreover, to improve the accuracy of the adaptive weights of individual NNs, GA is used to optimize the cluster centers. Empirical results in predicting carbon flux of Duke Forest reveal that GA-ANNE can predict the carbon flux more accurately than Radial Basis Function Neural Network (RBFNN), Bagging NN ensemble, and ANNE. ?? 2007 IEEE.
| Publication type | Conference Paper |
|---|---|
| Publication Subtype | Conference Paper |
| Title | Genetic algorithm based adaptive neural network ensemble and its application in predicting carbon flux |
| DOI | 10.1109/ICNC.2007.399 |
| Year Published | 2007 |
| Language | English |
| Publisher | IEEE |
| Contributing office(s) | Earth Resources Observation and Science (EROS) Center |
| Description | 5 p. |
| Larger Work Type | Book |
| Larger Work Subtype | Conference publication |
| Larger Work Title | Proceedings - Third International Conference on Natural Computation, ICNC 2007 |
| First page | 183 |
| Last page | 187 |
| Conference Title | 3rd International Conference on Natural Computation, ICNC 2007 |
| Conference Location | Haikou, China |
| Conference Date | Aug 24-27, 2007 |
| Google Analytic Metrics | Metrics page |