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新报告。根据新闻报道在澳门，中华人民共和国，由NewsRx编辑，研究表明，“广泛的研究几十年来，ANAMMO X的性能一直在不断提高，重点放在其操作上但这种基于参数的优化是困难的，因为它的数量庞大这些因素的可能组合和多维射线。利用机器学习算法应用贝叶斯非参数一般回归(BNGR)对已发表的ANAMM OX数据进行辨识。y 11个运行参数和环境参数中可能的调节变量（反应器）类型、混合类型、工作容积、水力停留时间、温度、进水pH、亚硝酸盐、铵、硝酸盐浓度、氮损失率和有机浓度。
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 Macau, People’s Republic of C hina, by NewsRx editors, research stated, “Extensive studies onimproving anammo x performance have taken place for decades with particular focuses on its operat ionaland environmental factors, but such parameter-based optimization is diffic ult, because of the sheer numberof possible combinations and multidimensional a rrays of these factors. Utilizing machine-learning algorithmand published anamm ox data, Bayesian nonparametric general regression (BNGR) was applied to identify the possible governing variable(s) from among 11 operating and environmental p arameters: reactortype, mixing type, working volume, hydraulic retention time, temperature, influent pH, nitrite, ammonium,nitrate concentration, nitrogen loa ding rate, and organic concentration.”
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