摘要
由一名新闻记者-机器人与机器学习每日新闻的工作人员新闻编辑-调查人员发布了关于机器学习的新报告。根据NewsRx记者从印度马哈拉施特拉邦发回的新闻报道，研究表明：“选择合适数量的INPU Ts，即所谓的滑动窗口长度(SWL)，用于进水水质时间序列预测，多年来一直是一个研究课题。然而，以往的研究忽略了SWL的选择，而是采用了一种试错法或优化算法。”
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators publish new report on Machine Learn ing. According to news reporting originating from Maharashtra, India, by NewsRx correspondents, research stated, “The selection of an appropriate number of inpu ts, known as Sliding window length (SWL) for influent wastewater quality time se ries forecasting, has been a topic of research for several years. However, previ ous studies have overlooked the SWL selection and instead used a trial -and -err or approach or optimization algorithms.”
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