Daily Prediction of PM 10 using Radial Basis Function and Generalized Regression Neural Network

作者: Vibha Yadav , Satyendra Nath

DOI: 10.1109/RAETCS.2018.8443887

关键词:

摘要: Due to urbanization and population growths air pollutant (AP) are increasing drastically. Therefore, predictive AP models have become an important tool provide quality management for the site. In this study prediction of PM10 is performed using radial basis function neural network (RBFNN) generalized regression (GRNN). For daily average value PM2.5, NO, Benzene, vertical wind speed Ardali bazar in Varanasi, India considered. RBFNN GRNN incorporates input variables as target variable PM10. It found that predict better than multiple linear models.

参考文章(9)
E. Jach-Szakiel, J. Skrzypski, Neural network prediction models as a tool for air quality management in cities Environment Protection Engineering. ,vol. 34, pp. 129- 137 ,(2008)
Konstantinos P. Moustris, Ioannis C. Ziomas, Athanasios G. Paliatsos, 3-Day-Ahead Forecasting of Regional Pollution Index for the Pollutants NO2, CO, SO2, and O3 Using Artificial Neural Networks in Athens, Greece Water Air and Soil Pollution. ,vol. 209, pp. 29- 43 ,(2010) , 10.1007/S11270-009-0179-5
Wan Rozita Wan Mahiyuddin, Mazrura Sahani, Rasimah Aripin, Mohd Talib Latif, Thuan-Quoc Thach, Chit-Ming Wong, Short-term effects of daily air pollution on mortality Atmospheric Environment. ,vol. 65, pp. 69- 79 ,(2013) , 10.1016/J.ATMOSENV.2012.10.019
Mahad S. Baawain, Aisha S. Al-Serihi, Systematic Approach for the Prediction of Ground-Level Air Pollution (around an Industrial Port) Using an Artificial Neural Network Aerosol and Air Quality Research. ,vol. 14, pp. 124- 134 ,(2014) , 10.4209/AAQR.2013.06.0191
Kanchan Prasad, Amit Kumar Gorai, Pramila Goyal, Development of ANFIS models for air quality forecasting and input optimization for reducing the computational cost and time Atmospheric Environment. ,vol. 128, pp. 246- 262 ,(2016) , 10.1016/J.ATMOSENV.2016.01.007
Jianjun He, Ye Yu, Yaochen Xie, Hongjun Mao, Lin Wu, Na Liu, Suping Zhao, Numerical Model-Based Artificial Neural Network Model and Its Application for Quantifying Impact Factors of Urban Air Quality Water Air and Soil Pollution. ,vol. 227, pp. 235- ,(2016) , 10.1007/S11270-016-2930-Z
Weifu Ding, Jiangshe Zhang, Yee Leung, Prediction of air pollutant concentration based on sparse response back-propagation training feedforward neural networks Environmental Science and Pollution Research. ,vol. 23, pp. 19481- 19494 ,(2016) , 10.1007/S11356-016-7149-4
JK Shrivastava, Umesh Pendharker, Sarita Sharma, Navneeta lal Benjamin, Air quality prediction using artificial neural network International Journal of Chemical Studies. ,vol. 2, pp. 07- 09 ,(2014)