Determination of the Optimal Training Principle and Input Variables in Artificial Neural Network Model for the Biweekly Chlorophyll-a Prediction: A Case Study of the Yuqiao Reservoir, China

Yu Liu; Du-Gang Xi; Zhao-Liang Li

doi:10.1371/journal.pone.0119082

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Open Access

Peer-reviewed

Research Article

Determination of the Optimal Training Principle and Input Variables in Artificial Neural Network Model for the Biweekly Chlorophyll-a Prediction: A Case Study of the Yuqiao Reservoir, China

Yu Liu,

Affiliations Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China
⨯
Du-Gang Xi,

Affiliations The PLA Information Engineering University, Zhengzhou, China, Naval Institute of Hydrographic Surveying and Charting, Tianjin, China
⨯
Zhao-Liang Li

* E-mail: lizhaoliang@caas.cn

Affiliations Key Laboratory of Agri-informatics, Ministry of Agriculture / Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China, ICube, UdS, CNRS, 300 boulevard Sebastien Brant, CS 10413, 67412 Illkirch, France
⨯

Determination of the Optimal Training Principle and Input Variables in Artificial Neural Network Model for the Biweekly Chlorophyll-a Prediction: A Case Study of the Yuqiao Reservoir, China

Yu Liu,
Du-Gang Xi,
Zhao-Liang Li

Published: March 13, 2015
https://doi.org/10.1371/journal.pone.0119082

About the Authors

Yu Liu

Affiliations Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China

Du-Gang Xi

Affiliations The PLA Information Engineering University, Zhengzhou, China, Naval Institute of Hydrographic Surveying and Charting, Tianjin, China

Zhao-Liang Li

* E-mail: lizhaoliang@caas.cn

Affiliations Key Laboratory of Agri-informatics, Ministry of Agriculture / Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China, ICube, UdS, CNRS, 300 boulevard Sebastien Brant, CS 10413, 67412 Illkirch, France

Competing Interests

The authors have declared that no competing interests exist.

Author Contributions

Conceived and designed the experiments: YL DGX. Performed the experiments: YL. Analyzed the data: YL ZLL. Contributed reagents/materials/analysis tools: ZLL. Wrote the paper: YL DGX. Designed the software used in analysis: DGX.

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Principal component analysis
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