watex: machine learning research in water exploration
发布时间：2023-10-22
点击次数：
DOI码：10.1016/j.softx.2023.101367
发表刊物：Water Resources Management
关键字：Python, machine learning, algorithms, hydro-geophysics, water
摘要：Water exploration is a scientific domain mostly devoted to the hydro-geophysics field. For instance, geophysical methods such as direct-current, electromagnetic (EM), and logging are primarily used in companionship with pure hydrogeological techniques to propose the right location for drilling operations and determine the permeability coefficient (k) parameter. Unfortunately, despite this combination, unsuccessful, unsustainable boreholes are persisting and the k parameter collection remains difficult and costly thereby creating a huge loss for funders, geophysical and drilling ventures. watex library brings efficient algorithms and smart approaches to solve these issues. Indeed, the recovery of loss EM signals, the automatic location detection for drilling operations, the prediction of flow rate, and the mixture learning strategy using machine learning are some sustainable solutions developed by watex to reduce the numerous losses for future hydro-geophysical engineering projects.
合写作者：Liu Jianxin
第一作者：Kouao Laurent Kouadio
论文类型：期刊论文
通讯作者：Liu Rong
文献类型：J
卷号：22
页面范围：101367
是否译文：否
发表时间：2023-03-16
收录刊物：SCI、EI