摘要
由一名新闻记者兼机器人与机器学习的工作人员新闻编辑每日新闻-一项关于机器学习的新研究现在已经可用。根据NewsRx记者源自英国雷丁的新闻报道，研究表明：“城市热岛(UHI)效应加剧了城市近地表气温（T）的极端情况，对人类健康、建筑能耗和基础设施产生负面影响。”模拟控制T的邻域尺度变化的复杂过程既困难又昂贵。我们使用机器学习(ML)将英国气象局业务区域预测模型(UKV)所做的正确和缩小的T预测偏差到英国伦敦100米水平网格长度。"
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news reporting originating in Reading, United Kingdom, by NewsRx journalists, research stated, “The urban heat island (UHI) effect exac erbates near-surface air temperature (T) extremes in cities, with negative impac ts for human health, building energy consumption and infrastructure. Using conve ntional weather models, it is both difficult and computationally expensive to si mulate the complex processes controlling neighbourhoodscale variation of T. We use machine learning (ML) to bias correct and downscale T predictions made by th e Met Office operational regional forecast model (UKV) to 100 m horizontal grid length over London, UK.”
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