《International Journal of Sediment Research》杂志刊登“利用人工神经网络评估输沙公式”

 
作者：Chih Ted YANG, Reza MARSOOLI, and Mohammad Taghi AALAMI
刊物：《International Journal of Sediment Research》，2009年，第24卷，274-286页
关键词：人工神经网络；总床沙质输沙；泥沙输移公式。
摘要：根据实测数据计算表明，不同的输沙公式存在明显差异，部分公式中引用的参数估算泥沙输移总量时较其他公式更有效。在本研究中，利用输沙公式中的4个参数构建了人工神经网络（ANN）模型。人工神经网络模型能够揭示诸如泥沙输移过程等自然界中隐藏的客观规律。对ANN与其他泥沙输沙模型进行比较，以明确各个变量的重要性，并以此改进泥沙输移公式。以平均流速、水面斜率、平均水深和中值粒径作为主要参数对ANN进行构建，来计算输沙率。引用250个样本对ANN进行校对，采用24套数据对ANN与其他知名泥沙输移公式进行对比。对比结果表明，本文开发的模型使用最少参数，能够简单可靠的预测全沙输移率和总床沙质输移率。公式精度依次为Yang（1973），Laursen (1958)，Engelund and Hansen (1972)，Ackers and White (1973)和Toffaleti (1969)。该结果与美国土木工程师协会（1982）根据和本研究不同的实验与实测资料得出的结果相近。研究结果还表明，在估计总床沙质输移方面，基于物理意义下对力进行推导的泥沙输移公式更为准确。

Evaluation of total load sediment transport formulas using ANN

Authors:Chih Ted YANG, Reza MARSOOLI, and Mohammad Taghi AALAMI
Journal: International Journal of Sediment Research, Vol. 24, No. 3, 2009, pp. 274-286
Key words:Artificial Neural Network (ANN), Total bed material load, Sediment transport formulas
Abstract: The calculated results from various sediment transport formulas often differ from each other and from measured data. Some parameters in the sediment transport formulas are more effective than others to estimate total sediment load. In this study, an Artificial Neural Network (ANN) model is trained using four dominant parameters of sediment transport formulas. ANN models are able to reveal hidden laws of natural phenomena such as sediment transport process. The results of ANN and some total bed material load sediment transport formulas have been compared to indicate the importance of variables which can be used in developing sediment transport formulas. To train ANN, average flow velocity, water surface slopes, average flow depth, and median particle diameter are used as dominant parameters to estimate total bed material load. Two hundreds and fifty samples are used to train the ANN model. Twenty-four sets of field data not used in the training nor calibration of ANN are used to compare or verify the accuracy of ANN and some well-known total bed material load formulas. The test results show that the ANN model developed in this study using minimum number of dominant factors is a reliable and uncomplicated method to predict total sediment transport rate or total bed material load transport rate. Results show that the accuracy of formulas in descending order are those by Yang (1973), Laursen (1958), Engelund and Hansen (1972), Ackers and White (1973), and Toffaleti (1969). These results are similar to those made by ASCE (1982) based on laboratory and field data not used in this paper. Study results also show that the formulas based on physical laws of sediment transport, like those formulas that were developed based on power concept, are more accurate than other formulas for estimating total bed material sediment load in rivers.

原文链接：http://www.cnki.com.cn/Article/CJFDTotal-GJNS200903003.htm
翻译：苏昕；审稿：何凡