首页|Shandong University Reports Findings in Artificial Intelligence (Precise managem ent and control around the landfill integrating artificial intelligence and grou ndwater pollution risks)
Shandong University Reports Findings in Artificial Intelligence (Precise managem ent and control around the landfill integrating artificial intelligence and grou ndwater pollution risks)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews ; New research on Artificial Intelligence is the su bject of a report. According to news reportingoriginating in Qingdao, People’s Republic of China, by NewsRx journalists, research stated, “The Landfillplays a n important role in urban development and waste disposal. However, landfill leac hate may alsobring more serious pollution and health risks to the surrounding g roundwater environment.”The news reporters obtained a quote from the research from Shandong University, “Compared withother areas, the area around the landfill needs more precise mana gement. To solve this problem, basedon the ‘pressure-state-response’ framework, a method for the identification and evaluation of groundwaterpollution around the landfill was constructed. The LPI method was used to assess the contaminatio npotential of the leachate. The comprehensive quality of groundwater was evalua ted by the entropy-AHP water quality assessment method, sodium adsorption ratio and sodium percentage. The probabilistichealth risks of groundwater were assess ed based on a Monte Carlo algorithm. The sources of pollutantswere identified b y comprehensively using the PCA-APCS-MLR model and the PMF model. Finally, thes elf-organizing map algorithm and the Kmeans algorithm were integrated to enhance the precision ofgroundwater management and control measures. The results showe d that the leachate of the landfillwas in the mature stage, and the concentrati on of inorganic substances was relatively high. Leachatehad the potential to co ntaminate surrounding groundwater. The groundwater quality of 68.14% of thestudy area was in the poor or lower level. The groundwater near the landf ill was unsuitable not onlyfor drinking but also for irrigation purposes. Cl wa s the main non-carcinogenic risk factor. Reducingpollutant concentration and co ntrolling exposure time are effective strategies for mitigating health riskscau sed by high-concentration pollutants (Cl, NO) and low-concentration pollutants ( F), respectively. Thegroundwater around the landfill was jointly affected by si x pollution sources. The PMF model has betteranalytical ability in mixed pollut ion areas.”
QingdaoPeople’s Republic of ChinaAsi aAlgorithmsArtificial IntelligenceEmerging TechnologiesMachine LearningRisk and Prevention
NETL
NSTL
