Forecasting Air Pollution by Adaptive Neuro Fuzzy Inference System
作者： Masoomeh Zeinalnezhad , Abdoulmohammad Gholamzadeh Chofreh , Feybi Ariani Goni , Jiri Jaromir Klemes , Ardalan Mohammadi Darvishvand
DOI: 10.23919/SPLITECH.2019.8783075
关键词:
摘要: Air pollution causes a variety of adverse effects on humans such as illness or even death and damages the living organisms natural environment. This environmental issue needs to be controlled using various application technology estimate composition multiple pollutants in atmosphere for specified time location. The present study aims develop system air forecasting an adaptive neuro-fuzzy inference system. method is type artificial neural network that integrates both networks fuzzy logic principles. calculations include four phases including implement system, enter parameters, start learning process, verify processed data. As sample, concentrations atmospheric pollutant data recorded by sensors. predicts indicator levels, carbon monoxide, sulfur dioxide, nitrogen oxides, trioxygen. analysis results reveal mean absolute error less than 15 %.
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