摘要
机器人与机器学习每日新闻的一位新闻记者兼新闻编辑发表了关于人工智能的新研究结果。根据NewsRx记者来自阿尔及利亚阿尔及尔的新闻报道，研究表明，"智能家居整合了七种传感器，以促进信息交流和任务执行"。我们的新闻记者从科技大学Houari Boumediene(USTHB)的研究中获得了一句话：“此外，随着物联网(IoT)平台的发展，”本文采用机器学习的方法对智能家居的能耗和效率进行了全面的分析,提出了两种改进的集成模型来提高智能家居的能耗性能。第一个是基于排名权重平均的虚拟集成模型，结合了以下基本的机器学习技术：决策树(DT)、随机森林(RF)和E Xtreme Gradient Boosting(XGB)。"
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New study results on artificial intell igence have been published. According to news reporting originating from Algiers , Algeria, by NewsRx correspondents, research stated, “Smart homes integrate sev eral sensors to facilitate information exchange and the execution of tasks.” Our news journalists obtained a quote from the research from University of Scien ce and Technology Houari Boumediene (USTHB): “In addition, with the development of the Internet of Things (IoT) platforms, the control of appliances and remote devices has become possible. This sensor collects data in real time to closely m onitor the devices of a user’s household. The present study employs a machine le arning methodology to perform a global analysis of energy consumption and effici ency in smart homes. In This work we propose two advanced ensemble models to imp rove the performance of energy consumption in smart homes, the first one is a vo ting ensemble model based on a ranking weight averaging that combines following basic machine learning techniques: decision tree (DT), random forest (RF), and e Xtreme Gradient Boosting (XGB).”
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