首页|Southern University of Science and Technology (SUSTech) Researcher Releases New Study Findings on Machine Learning (Screening and Optimization of Soil Remediati on Strategies Assisted by Machine Learning)

Southern University of Science and Technology (SUSTech) Researcher Releases New Study Findings on Machine Learning (Screening and Optimization of Soil Remediati on Strategies Assisted by Machine Learning)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on ar tificial intelligence. According to news originating from Southern University of Science and Technology (SUSTech) by NewsRx correspondents, research stated, "A numerical approach assisted by machine learning was developed for screening and optimizing soil remediation strategies." Funders for this research include National Key Research And Development Program of China; Program For Guangdong Introducing Innovative And Entrepreneurial Teams ; High Level of Special Funds. Our news journalists obtained a quote from the research from Southern University of Science and Technology (SUSTech): "The approach includes a reactive transpor t model for simulating the remediation cost and effect of applicable remediation technologies and their combinations for a target site. The simulated results we re used to establish a relationship between the cost and effect using a machine learning method. The relationship was then used by an optimization method to pro vide optimal remediation strategies under various constraints and requirements f or the target site. The approach was evaluated for a site contaminated with both arsenic and polycyclic aromatic hydrocarbons at a former shipbuilding factory i n Guangzhou City, China. An optimal strategy was obtained and successfully imple mented at the site, which included the partial excavation of the contaminated so ils and natural attenuation of the residual contaminated soils."

Southern University of Science and Techn ology (SUSTech)CyborgsEmerging TechnologiesMachine Learning

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Jun.18)