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-机器学习的新研究是一篇报道的主题。据新闻报道来自中国人民代表大会上海，由NewsRx记者报道，研究称，“基于”厨房用四台全尺寸干式厌氧消化池1.5年的运行数据本研究采用了八种典型的机器学习算法来区分食物垃圾处理的最佳沼气预测模型及基于VFA/ALK比值的软测量研究在所有八个人中经过测试的模型，CatBoost(CB)算法在预测方面表现出优异的性能精度和模型拟合"。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to newsoriginating from Shanghai, People’s Rep ublic of China, by NewsRx correspondents, research stated, “Basedon operational data collected over 1.5 years from four full-scale dry anaerobic digesters used for kitchenfood waste treatment, this study adopted eight typical machine lear ning algorithms to distinguish the bestbiogas prediction model and to develop a soft sensor based on the VFA/ALK ratio. Among all the eighttested models, the CatBoost (CB) algorithm demonstrated superior performance in terms of predictionaccuracy and model fitting.”
NETL
NSTL