This research was funded by the National Natural Science Foundation of China (Nos. 41672263, 41072199), the Key Program of the Natural Science Foundation of Hubei Province in China (No. 2015CFA134) and the Key Program of the Science & Technology Plan of Hunan Province in China (No. 2016SK2088). The authors gratefully thank the institute of Space Information Technology and the Key Laboratory for Digital Dongting Lake basin of Hunan Province of Central South University of Forestry and Technology and the Institute of Remote Sensing and Space Information Science and the Key Laboratory for Digital Basin Science and Technology of Hubei Province of Huazhong University of Science and Technology for providing the facilities during this research work and for supporting the related researches. We would also like to thank the China Meteorological Administration for providing the metrological data, the Research Center for Adaptive Data Analysis of National Central University for providing the EEMD software and the Google company for providing the TensorFlow neural network framework used for experiments. The authors also greatly appreciate the anonymous reviewers and academic editor for their careful comments and valuable suggestions to improve the manuscript.
Acknowledgments: The authors gratefully thank the institute of Space Information Technology and the Key Laboratory for Digital Dongting Lake basin of Hunan Province of Central South University of Forestry and Technology and the Institute of Remote Sensing and Space Information Science and the Key Laboratory for Digital Basin Science and Technology of Hubei Province of Huazhong University of Science and Technology for providing the facilities during this research work and for supporting the related researches. We would also like to thank the China Meteorological Administration for providing the metrological data, the Research Center for Adaptive Data Analysis of National Central University for providing the EEMD software and the Google company for providing the TensorFlow neural network framework used for experiments. The authors also greatly appreciate the anonymous reviewers and academic editor for their careful comments and valuable Int.J.suEnvirggeson.tionRes.s toPublicimproHealthve the2018man, 15us,c1032ript. 18 of 23
Funding: This research was funded by the National Natural Science Foundation of China (Nos. 41672263, 41072199), the Key Program of the Natural Science Foundation of Hubei Province in China (No. 2015CFA134) and the Key Program of the Science & Technology Plan of Hunan Province in China (No. 2016SK2088).
Acknowledgments: The authors gratefully thank the institute of Space Information Technology and the Key Laboratory for Digital Dongting Lake basin of Hunan Province of Central South University of Forestry and Technology and the Institute of Remote Sensing and Space Information Science and the Key Laboratory for Digital Basin Science and Technology of Hubei Province of Huazhong University of Science and Technology for providing the facilities during this research work and for supporting the related researches. We would also like to thank the China Meteorological Administration for providing the metrological data, the Research Center for Adaptive Data Analysis of National Central University for providing the EEMD software and the Google company for providing the TensorFlow neural network framework used for experiments. The authors also greatly appreciate the anonymous reviewers and academic editor for their careful comments and valuable suggestions to improve the manuscript.
