首页|Nankai University Researcher Provides New Insights into Machine Learning (Machin e Learning Models for Predicting Bioavailability of Traditional and Emerging Aro matic Contaminants in Plant Roots)
Nankai University Researcher Provides New Insights into Machine Learning (Machin e Learning Models for Predicting Bioavailability of Traditional and Emerging Aro matic Contaminants in Plant Roots)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News-A new study on artificial intelligence is now available. According to news originatingfrom Tianjin, People's Republic of China, by NewsRx correspondents, research stated, "To predict thebehavior o f aromatic contaminants (ACs) in complex soil-plant systems, this study develope d machine learning (ML) models to estimate the root concentration factor (RCF) o f both traditional (e.g., polycyclicaromatic hydrocarbons, polychlorinated biph enyls) and emerging ACs (e.g., phthalate acid esters, arylorganophosphate ester s)."Funders for this research include The Major Scientific And Technological Innovat ion Project of ShandongProvince.
Nankai UniversityTianjinPeople's Rep ublic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning
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