Environmental Health Engineering and Management Journal

en Modeling the concentration of suspended particles by fuzzy inference system (FIS) and adaptive neuro-fuzzy inference system (ANFIS) techniques: A case study in the metro stations تخصصي Special مقاله اصیل Original Article <div style="text-align: justify;">Background: Today, the usage of artificial intelligence systems and computational intelligence is increasing. This study aimed to determine the fuzzy system algorithms to model and predict the amount of air pollution based on the measured data in subway stations. Methods: In this study, first, the effective variables on the concentration of particulate matter were determined in metro stations. Then, PM2.5, PM10, and total size particle (TSP) concentrations were measured. Finally, the particles’ concentration was modeled using fuzzy systems, including the fuzzy inference system (FIS) and adaptive neuro-fuzzy inference system (ANFIS). Results: It was revealed that FIS with modes gradient segmentation (FIS-GS) could predict 76% and ANFIS-FCM with modes of clustering and post-diffusion training algorithm (CPDTA) could predict 85% of PM2.5, PM10, and TSP particle concentrations. Conclusion: According to the results, among the models studied in this work, ANFIS-FCM-CPDTA, due to its better ability to extract knowledge and ambiguous rules of the fuzzy system, was considered a suitable model.  </div> Artificial intelligence, Railroads, Cluster analysis, Air pollution, Particulate matter 311 319 http://ehemj.com/browse.php?a_code=A-10-1-312&slc_lang=en&sid=1 Zahra Sadat Mousavi Fard mossavizahra@modares.ac.ir 100319475328460013510 100319475328460013510 No Department of Occupational Health Engineering, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran Hassan Asilian Mahabadi Asilia_h@modares.ac.ir 100319475328460013511 100319475328460013511 Yes Corresponding author: Department of Occupational Health Engineering, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran Farahnaz Khajehnasiri khajenasiri@tums.ac.ir 100319475328460013512 100319475328460013512 No Department of Community Medicine, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran Mohammad Amin Rashidi rashidy.mohamadamin@gmail.com 100319475328460013513 100319475328460013513 No Student Research Committee, Department of Occupational Health and Safety, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran