پیش‌بینی آلودگی هوای شهر تهران با استفاده از ترکیب شبکة عصبی فازی‌ـ تطبیقی وآنالیز مؤلفة اصلی

نوع مقاله : علمی - پژوهشی

نویسندگان

1 دانشجوی دکترای سیستم اطلاعات مکانی، دانشکدة مهندسی ژئودزی و ژئوماتیک دانشگاه صنعتی خواجه‌ نصیرالدین طوسی

2 دانشیار دانشکدة مهندسی ژئودزی و ژئوماتیک، دانشگاه صنعتی خواجه‌ نصیرالدین طوسی

3 استادیار دانشکدة مهندسی ژئودزی و ژئوماتیک، دانشگاه صنعتی خواجه‌ نصیرالدین طوسی

4 عضو هیئت علمی گروه مهندسی عمران، نقشه برداری، دانشکدة فنی و مهندسی، دانشگاه بجنورد

چکیده

رشد و توسعة شهری و افزایش استفاده از وسایل نقلیه در سال‌های اخیر منجر به افزایش آلودگی هوا، به‌ویژه در شهر‌های بزرگ و صنعتی، شده است. با توجه به آثار نامطلوب آلودگی هوا در سلامت انسان‌ها و دیگر جانداران، پیش‌بینی و مدل‌سازی این پدیدة پیچیده از دغدغه‌های اصلی محققان در سال‌های اخیر بوده است. هدف این تحقیق طراحی سیستمی است به‌منظور پیش‌بینی آلودگی هوا، طی 24 ساعت آینده، تا با شناسایی مناطق آلوده، به مدیران و برنامه‌ریزان شهری برای کنترل و کاهش میزان آلاینده‌ها کمک کند. در سیستم طراحی‌شده، از ترکیب آنالیز مؤلفة اصلی و شبکة عصبی فازی‌– تطبیقی (PCA-ANFIS)، به‌منظور پیش‌بینی آلودگی هوا در فصل‌های متفاوت، استفاده شده است. در این سیستم، داده‌های هواشناسی و غلظت آلاینده‌ها در روزهای گذشته، برای پیش‌بینی آلودگی هوای شهر تهران در 24 ساعت آینده، به‌کار رفته است. همچنین، از پارامتر‌های مکانی مانند ارتفاع، توپوگرافی سطح زمین و فاصله از جاده به‌منظور مدل‌سازی مکانی پراکندگی آلودگی هوا استفاده شده است. نتایج حاصل از مقایسة روش ترکیبی PCA-ANFIS با روش ANFIS دقت و سرعت بالاتر مدل ترکیبی طراحی‌شده را، به‌نسبت روش ANFIS در پیش‌بینی آلودگی هوا طی 24 ساعت آینده، بیان می‌کند. 

کلیدواژه‌ها

عنوان مقاله [English]

Prediction of Tehran Air Pollution Using PCA-ANFIS Method

نویسندگان [English]

  • Z Ghaemi 1
  • M Taleai 2
  • M Farnaghi 3
  • G Javadi 4
1 PH.d. student of geographic information systems, Faculty of Geodesy and Geomatics, K.N.Toosi University of Technology
2 Associate Prof., Faculty of Geodesy and Geomatics, K.N.Toosi University of Technology
3 Assistant Prof., Faculty of Geodesy and Geomatics, K.N.Toosi University of Technology
4 Faculty Member of Geomatics Ingineering University of Bojnourd
چکیده [English]

Urban growth and increased use of vehicles have led to an increase in air pollution, especially in large and industrialized cities in recent years. Because of the adverse effect of air pollution on human and other creatures, prediction and modeling of this complex phenomenon have the main concern of researchers during the last years. The purpose of this research is to design an air pollution prediction system to identify the contaminated areas in order to help the urban managers and planners to control and reduce the amount of contaminants. In the proposed system in order to predict the air pollution in different seasons, PCA-ANFIS model has been used. In this system, meteorological data and concentrations of pollutants are used to predict air pollution in Tehran over the next 24 hours. In addition, spatial parameters including height, topography and distance from the road are used to model the spatial distribution of air pollution. Comparing the results of PCA-ANFIS and ANFIS methods prove that the proposed model obtained higher accuracy in less processing time.

کلیدواژه‌ها [English]

  • Urban air pollution prediction
  • Adaptive nero fuzzy inference system
  • Principal Component Analysis (PCA)
  • GIS

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نشریه سنجش از دور و GIS ایران
دوره 9، شماره 3 - شماره پیاپی 3
اردیبهشت 1396
صفحه 45-70

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