Comparative study of multilayer perceptron-stochastic gradient descent and gradient boosted trees for predicting daily suspended sediment load: The case study of the Mississippi River,U.S.期刊界 All Journals 搜尽天下杂志传播学术成果专业期刊搜索期刊信息化学术搜索

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Comparative study of multilayer perceptron-stochastic gradient descent and gradient boosted trees for predicting daily suspended sediment load: The case study of the Mississippi River,U.S.

Authors:	Sadra Shadkani Akram Abbaspour Saeed Samadianfard Sajjad Hashemi Amirhosein Mosavi Shahab S Band

Institution:	1. Department of Water Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran;2. Environmental Quality, Atmospheric Science and Climate Change Research Group, Ton Duc Thang University, Ho Chi Minh City, Viet Nam;3. Faculty of Environment and Labour Safety, Ton Duc Thang University, Ho Chi Minh City, Viet Nam;4. Institute of Research and Development, Duy Tan University, Da Nang, 550000, Viet Nam;5. Future Technology Research Center, College of Future, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin, 64002, Taiwan, China

Abstract:

Keywords:	Suspended sediment transport Ensemble learning Multilayer perceptron Stochastic gradient descent Machine learning
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