摘要
由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-调查人员发布马学习的新报告。根据新闻报道NewsRx e Ditors在摩洛哥Kenitra发表的研究报告称，“rabat-salé-kénitra”由于人口增长减少了对地下水的需求，摩洛哥区域面临着严峻的地下水挑战，农业扩张，以及长期干旱和气候变化的影响。本研究采用先进的机器学习模型，包括人工神经网络(ANN)，梯度提升(GB)支持向量回归(SVR)、决策树(DT)和随机森林(RF)预测地下水存储变化。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news reportingout of Kenitra, Morocco, by NewsRx e ditors, research stated, “The Rabat-Sal & eacute;-K & eacute;nitraregion of Morocco faces critical groundwater challenges due to incr easing demands from population growth,agricultural expansion, and the impacts o f prolonged droughts and climate change. This study employsadvanced machine lea rning models, including artificial neural networks (ANN), gradient boosting (GB), support vector regression (SVR), decision tree (DT), and random forest (RF), t o predict groundwaterstorage variations.”
NETL
NSTL