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Genetic algorithm based adaptive neural network ensemble and its application in predicting carbon flux

By:
, , , ,
DOI: 10.1109/ICNC.2007.399

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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.

Additional Publication Details

Publication type:
Conference Paper
Publication Subtype:
Conference Paper
Title:
Genetic algorithm based adaptive neural network ensemble and its application in predicting carbon flux
ISBN:
0769528759; 9780769528755
DOI:
10.1109/ICNC.2007.399
Volume
1
Year Published:
2007
Language:
English
Larger Work Title:
Proceedings - Third International Conference on Natural Computation, ICNC 2007
First page:
183
Last page:
187
Number of Pages:
5
Conference Title:
3rd International Conference on Natural Computation, ICNC 2007
Conference Location:
Haikou, Hainan
Conference Date:
24 August 2007 through 27 August 2007