论文信息 - Genetic Algorithm based Adaptive Neural Network Ensemble and Its Application in Predicting Carbon Flux

Genetic Algorithm based Adaptive Neural Network Ensemble and Its Application in Predicting Carbon Flux

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.

Yueming Hu | Qiang Chen | Yueju Xue | Shuguang Liu | Jingfeng Yang

[1] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.

[2] Xin Yao,et al. A constructive algorithm for training cooperative neural network ensembles , 2003, IEEE Trans. Neural Networks.

[3] Robert E. Schapire,et al. The strength of weak learnability , 1990, Mach. Learn..

[4] Thomas R. Loveland,et al. Contemporary Carbon Dynamics in Terrestrial Ecosystems in the Southeastern Plains of the United States , 2004 .

[5] Bruce K. Wylie,et al. Adaptive data-driven models for estimating carbon fluxes in the Northern Great Plains , 2007 .

[6] Teresa Bernarda Ludermir,et al. EFuNNs Ensembles Construction Using a Clustering Method and a Coevolutionary Genetic Algorithm , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[7] Changhua Hu,et al. Adaptive Neural Network Ensemble Algorithm , 2006, 2006 6th World Congress on Intelligent Control and Automation.

[8] Lars Niklasson,et al. Building Neural Network Ensembles using Genetic Programming , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

[9] Kagan Tumer,et al. Error Correlation and Error Reduction in Ensemble Classifiers , 1996, Connect. Sci..

[10] Joshua M. Uebelherr,et al. An evaluation of models for partitioning eddy covariance-measured net ecosystem exchange into photosynthesis and respiration , 2006 .