1- اجتهادی، م.، 1386، بررسی آلودگی هوای شهری به دلیل فرایندهای انتقال در خشکی با تاکید بر ذرات معلق و ارایه راهکارهای مدیریتی (مطاله موردی، تهران)، دهمین همایش بهداشت محیط .
2 - توکلی، م. و ع. اسماعیلی ساری، 1393، مقایسه عملکرد شبکه های عصبی مصنوعی و فازی تطبیقی در تخمین ذرات معلق تهران ، فصل نامه علوم و محیط زیست 75-2 .
3- رفیع پور، م.، ع. آل شیخ ، و. ع.، محمدی، ع. و ع. صادقی نیارکی، 1395، استفاده از شبکه بازگشتی NAR برای پیش بینی غلظت ذرات مونوکسید کربن، علوم و تکنولوژی محیط زیست، 18-3 .
4- عباس پور، ر.، 1396، پیش بینی غلظت آلاینده های مونوکسید کربن در کلان شهر تهران با استفاده از شبکه عصبی مصنوعی،19-5 .
5-Chatfield, C., 1989, The analysis of time series: An Introduction, 4th edition, Chapman and Hall, New York.
6-Dorffner, G., 1996, Neural networks for time series processing, Neural Network World 4(96), 447-68.
7- Elangasinghe, M., N. Singhal, K. Dirks and J. Salmond, 2014, Development of an ANN–based air pollution forecasting system with explicit knowledge through sensitivity analysis, Atmospheric Pollution Research, 5,696-708.
8-Fan, J.X., Q. Li and Y.J. Zhu, 2017, The space-time air pollution forecast model based on RNN study, Journal of Surveying and Mapping Science, 7, 80-87.
9-Ganesh S.S., S.H. Modali, S.R. Palreddy and P. Arulmozhivarman, 2017, Forecasting air quality index using regression models: A case study on Delhi and Houston, International Conference on Trends in Electronics and Informatics ,248-254.
10-Ganesh, S.S., P. Arulmozhivarman, and V.S.N.R. Tatavarti, 2018, Prediction of PM 2.5 using an ensemble of artificial neural networks and regression models, Journal of Ambient Intelligence and Humanized Computing,1-11.
11- Jang, J.S.R., N. Gulley, 1995, The fuzzy logic toolbox for use with MATLAB, The Mathworks Inc, Natick, MA.
12-Jiusheng, L., B. Zhenwu, 2003, Application of the neural network optical fiber temperature sensor probe design used in medical treatment, International Conference on Neural Networks and Signal Processing, Nanjing, pp. 389.
13-Nayak, P.C., K.P. Sudheer, D.M. Rangan and K.S. Ramasastri, 2005, Short term flood forecasting with a neuron fuzzy model , Water Resources Research,41(4),2517-2530.
14-Nelles, O., 2001, Nonlinear system identification, Springer, Berlin, Heidelberg.
15- Zemouri, R., R. Gouriveau and N. Zerhouni, 2010, Defining and applying prediction performance metrics on a recurrent NARX time series model, Neurocomputing, 73(13-15) ,2506-2521.
-10-Ganesh, S.S., P. Arulmozhivarman, and V.S.N.R. Tatavarti, 2018, Prediction of PM 2.5 using an ensemble of artificial neural networks and regression models, Journal of Ambient Intelligence and Humanized Computing,1-11.
11- Jang, J.S.R., N. Gulley, 1995, The fuzzy logic toolbox for use with MATLAB, The Mathworks Inc, Natick, MA.
12-Jiusheng, L., B. Zhenwu, 2003, Application of the neural network optical fiber temperature sensor probe design used in medical treatment, International Conference on Neural Networks and Signal Processing, Nanjing, pp. 389.
13-Nayak, P.C., K.P. Sudheer, D.M. Rangan and K.S. Ramasastri, 2005, Short term flood forecasting with a neuron fuzzy model , Water Resources Research,41(4),2517-2530.
14-Nelles, O., 2001, Nonlinear system identification, Springer, Berlin, Heidelberg.
15- Zemouri, R., R. Gouriveau and N. Zerhouni, 2010, Defining and applying prediction performance metrics on a recurrent NARX time series model, Neurocomputing, 73(13-15) ,2506-2521.