首页|Guangdong University of Technology Reports Findings in Machine Learning (Machine learning models for predicting thermal desorption remediation of soils contamin ated with polycyclic aromatic hydrocarbons)
Guangdong University of Technology Reports Findings in Machine Learning (Machine learning models for predicting thermal desorption remediation of soils contamin ated with polycyclic aromatic hydrocarbons)
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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 newsreporting from Guangzhou, People’s Repu blic of China, by NewsRx journalists, research stated, “Amongvarious remediatio n methods for organic-contaminated soil, thermal desorption stands out due to it sbroad treatment range and high efficiency. Nonetheless, analyzing the contribu tion of factors in complexsoil remediation systems and deducing the results und er multiple conditions are challenging, given thecomplexities arising from dive rse soil properties, heating conditions, and contaminant types.”
GuangzhouPeople’s Republic of ChinaA siaAromatic HydrocarbonsCyborgsCyclic HydrocarbonsEmerging TechnologiesHydrocarbonsMachine LearningOrganic Chemicals
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