首页|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 ...)
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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.”
TianjinPeople’s Republic of ChinaAsi aAnionsCyborgsEmerging TechnologiesMachine LearningPhosphatesPhospho ric Acids
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