空气质量预测的机器学习:随机森林分类器

Kasula Vaishnavi, Gummalla Sreya, Kishor Kumar Reddy, Anisha P R
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引用次数: 0

摘要

空气污染是指由于大气中存在对人类和其他生物体造成重大影响的物质而导致的空气污染。空气质量是多种元素综合作用的结果,包括化学反应、气象参数以及自然和人为(人类)排放物。研究表明,印度不同地区和城市的预报性能各不相同。利用随机森林算法,每年根据 PM2.5、PM10、NOx、CO、SO2、O3、NH3 和 NO2 等空气污染物,在印度多个地区预测空气质量指数桶。
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Machine Learning for Air Quality Prediction: Random Forest Classifier
Air Pollution is the contamination of air due to the presence of substances in the atmosphere that are major issue to human life as well as to the other living organisms. Air quality is the result of the composite interactions of many elements, including the chemical reactions, meteorological parameters, and emissions from natural & anthropogenic (man-kind). The study implies that the forecasting performance differs across diverse regions & cities in India. Utilization of the Random Forest algorithm to anticipate the air quality index bucket is done in multiple locations across India annually, depending on air pollutants like PM2.5, PM10, NOx, CO, SO2, O3, NH3, and NO2.
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