Ministry of Agriculture and Rural Affairs Reports Findings in Machine Learning ( Machine learning-driven prediction of phosphorus removal performance of metal-mo dified biochar and optimization of preparation processes considering water quali ty ...)
Ministry of Agriculture and Rural Affairs Reports Findings in Machine Learning ( Machine learning-driven prediction of phosphorus removal performance of metal-mo dified biochar and optimization of preparation processes considering water quali ty ...)
机器人与机器学习的新闻编辑每日新闻-机器学习的新研究是一篇报道的主题。根据来自中国人民广播公司天津的消息，NewsRx记者说，“基于水质条件和管理，”本研究利用机器学习方法对201年发表在Web of Science上的文献中的金属改性生物炭吸附磷酸盐的实验数据进行了分析。4-2023.”Our新闻记者引用了农业和农村事务部的研究，“使用六种机器学习模型，”预测了生物炭对磷酸盐的吸附能力和残磷浓度,通过超参数优化,梯度强化模型表现出较好的训练性能(R>0.96),金属负载量、盖液比和pH是影响生物炭吸附性能的关键因素,最佳制备参数表明,镁改性生物炭对磷酸盐的吸附能力最高(387～396 mg/g)。而镧改性生物炭的残余磷酸盐浓度最低(0 mg/L)。基于优化工艺参数的验证试验结果与模型参数密切一致。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news originating from Tianjin, People’s Repu blic of China, by NewsRx correspondents, research stated, “Based on water qualit y conditions and management, developing an optimized and targeted design approac h for metal-modified biochar is achievable through machine learning. This study leveraged machine learning to analyze experimental data on phosphate adsorption by metal-modified biochar from literature published in Web of Science during 201 4-2023.”Our news journalists obtained a quote from the research from the Ministry of Agr iculture and Rural Affairs, “Using six machine learning models, phosphate adsorp tion capacity of biochar and residual phosphate concentration were predicted. Fo llowing hyperparameter optimization, gradient boosting model exhibited superior training performance (R > 0.96). Metal load quantity, so lid-liquid ratio, and pH are key factors influencing adsorption performance. Opt imal preparation parameters indicated that Mg-modified biochar achieved the high est adsorption capacity (387-396 mg/g), while La-modified biochar displayed the lowest residual phosphate concentration (0 mg/L). The results of verification ex periments based on optimized process parameters closely aligned with model predi ctions.”
Key words
Tianjin/People’s Republic of China/Asi a/Anions/Cyborgs/Emerging Technologies/Machine Learning/Phosphates/Phospho ric Acids
NETL
NSTL