Estimation of sediment discharge using a tree-based model

IF 2.8 3区 环境科学与生态学 Q2 WATER RESOURCES
E. Jang, U. Ji, W. Yeo
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引用次数: 0

Abstract

ABSTRACT The model tree (MT) approach, a data mining technique used to analyse relationships between input and output variables in a disordered and large database, was adopted in this study to predict sediment discharge with field measurement data. The derived models were analysed for accuracy according to the goodness of fit based on training, testing, and modelling processes. When the flow velocity, depth, water surface slope, channel width, and median bed material were selected as the river’s system variables, the model results of sediment discharge resembled the measured values. The results demonstrate that developing and using the sediment discharge estimation with the MT constitutes the most effective method if long-term sediment data are of sufficient validity.
基于树模型的输沙量估算
摘要本研究采用模型树(MT)方法,一种用于分析无序大型数据库中输入和输出变量之间关系的数据挖掘技术,利用现场测量数据预测输沙量。根据训练、测试和建模过程的拟合优度,对导出的模型进行精度分析。当选择流速、深度、水面坡度、河道宽度和中值河床材料作为河流系统变量时,泥沙流量的模型结果与实测值相似。结果表明,如果长期泥沙数据具有足够的有效性,那么开发和使用MT估算泥沙流量是最有效的方法。
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来源期刊
CiteScore
6.60
自引率
11.40%
发文量
144
审稿时长
9.8 months
期刊介绍: Hydrological Sciences Journal is an international journal focused on hydrology and the relationship of water to atmospheric processes and climate. Hydrological Sciences Journal is the official journal of the International Association of Hydrological Sciences (IAHS). Hydrological Sciences Journal aims to provide a forum for original papers and for the exchange of information and views on significant developments in hydrology worldwide on subjects including: Hydrological cycle and processes Surface water Groundwater Water resource systems and management Geographical factors Earth and atmospheric processes Hydrological extremes and their impact Hydrological Sciences Journal offers a variety of formats for paper submission, including original articles, scientific notes, discussions, and rapid communications.
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