文章基本信息

标题：Locally weighted learning based hybrid intelligence models for groundwater potential mapping and modeling: A case study at Gia Lai province, Vietnam
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作者：Hoang Phan Hai Yen ; Binh Thai Pham ; Tran Van Phong 等
期刊名称：Geoscience Frontiers
印刷版ISSN：1674-9871
出版年度：2021
卷号：12
期号：5
页码：1-15
DOI：10.1016/j.gsf.2021.101154
语种：English
出版社：Elsevier
摘要：AbstractThe groundwater potential map is an important tool for a sustainable water management and land use planning, particularly for agricultural countries like Vietnam. In this article, we proposed new machine learning ensemble techniques namely AdaBoost ensemble (ABLWL), Bagging ensemble (BLWL), Multi Boost ensemble (MBLWL), Rotation Forest ensemble (RFLWL) with Locally Weighted Learning (LWL) algorithm as a base classifier to build the groundwater potential map of Gia Lai province in Vietnam. For this study, eleven conditioning factors (aspect, altitude, curvature, slope, Stream Transport Index (STI), Topographic Wetness Index (TWI), soil, geology, river density, rainfall, land-use) and 134 wells yield data was used to create training (70%) and testing (30%) datasets for the development and validation of the models. Several statistical indices were used namely Positive Predictive Value (PPV), Negative Predictive Value (NPV), Sensitivity (SST), Specificity (SPF), Accuracy (ACC), Kappa, and Receiver Operating Characteristics (ROC) curve to validate and compare performance of models. Results show that performance of all the models is good to very good (AUC: 0.75 to 0.829) but the ABLWL model with AUC = 0.89 is the best. All the models applied in this study can support decision-makers to streamline the management of the groundwater and to develop economy not only of specific territories but also in other regions across the world with minor changes of the input parameters.Graphical abstractDisplay OmittedHighlights•Groundwater potential was estimated using 5 machine learning models.•Sixty Sixty seven wells were used for modeling.•Eleven groundwater predictors were used to estimate the potential.•AdaBoost - Locally Weighted Learning was the most performant ensemble model.•Groundwater potential maps achieved a good and very good prediction accuracy.
关键词：KeywordsLocally weighted learningHybrid modelsGroundwater potentialGISVietnam