增强树算法和新的数据预处理技术在预测土耳其底格里斯盆地前一天流量值中的应用

IF 2.4 3区 环境科学与生态学 Q2 ENGINEERING, CIVIL
Okan Mert Katipoğlu , Metin Sarıgöl
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引用次数: 0

摘要

精确的流量预测在水资源管理、水工结构设计以及几乎所有与水和水资源利用有关的问题中都非常有用,尤其是在近年来不断增加的干旱地区。由于水是所有生命的来源,是人类赖以生存的最重要的基本要素,因此流量预测研究的重要性与日俱增。本研究将增强树(BT)模型与鲁棒经验模式分解、经验模式分解,带自适应噪声的完全集成经验模式分解以及经验小波变换和变分模式分解相结合,用于预测日均流量数据。在模型设置中输入历史流量数据时,使用一天交付周期流量数据作为目标。70%的数据保留用于训练,其余用于测试。使用5倍交叉验证技术来解决过拟合问题。确定系数、均方误差、Nash-Sutcliffe效率和百分比偏差统计标准以及泰勒图、极坐标图、散射图和小提琴图用于确定算法的成功率。在研究的最后,发现最成功的流量预测是用基于变分模式分解的BT混合方法进行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of boosted tree algorithm with new data preprocessing techniques in the forecasting one day ahead streamflow values in the Tigris basin, Türkiye

Accurate streamflow forecasting is very useful in water resources management, design of hydraulic structures, and almost all issues related to the use of water and water resources, especially in arid regions that have increased in recent years. Since water is the source of all life and the most important basic element for humanity to continue its life, streamflow prediction studies increase its importance daily. This research combined the boosted tree (BT) model with robust empirical mode decomposition, empirical mode decomposition, complete ensemble empirical mode decomposition with adaptive noise, empirical wavelet transforms and variational mode decomposition for predicting daily average streamflow data. While historical streamflow data was input in the model's setup, one-day lead-time streamflow data was used as the target. 70% of the data is reserved for training and the rest for testing. 5-fold cross-validation technique was used to solve the over-fitting problem. The coefficient of determination, mean squared error, Nash-Sutcliffe efficiency and percent bias statistical criteria and Taylor diagrams, polar plot, scattering diagram, and violin plot were used to determine the algorithm's success. At the end of the study, it was found that the most successful streamflow predictions were made with the variational mode decomposition-based BT hybrid approach.

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来源期刊
Journal of Hydro-environment Research
Journal of Hydro-environment Research ENGINEERING, CIVIL-ENVIRONMENTAL SCIENCES
CiteScore
5.80
自引率
0.00%
发文量
34
审稿时长
98 days
期刊介绍: The journal aims to provide an international platform for the dissemination of research and engineering applications related to water and hydraulic problems in the Asia-Pacific region. The journal provides a wide distribution at affordable subscription rate, as well as a rapid reviewing and publication time. The journal particularly encourages papers from young researchers. Papers that require extensive language editing, qualify for editorial assistance with American Journal Experts, a Language Editing Company that Elsevier recommends. Authors submitting to this journal are entitled to a 10% discount.
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