A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Prediction of Ambient PM10 and Toxic Metals Using Artificial Neural Networks
In this study, an artificial neural network is employed to predict the concentration of ambient respirable particu-late matter (PM10) and toxic metals observed in the city of Jaipur, India. A feed-forward network with a back-propagation learning algorithm is used to train the neural network the behavior of the data patterns. The meteorological variables of wind speed, wind direction, relative humidity, temperature, and time are taken as input to the network. The results indicate that the network is able to predict concentrations of PM10 and toxic metals quite accurately.
Prediction of Ambient PM10 and Toxic Metals Using Artificial Neural Networks
In this study, an artificial neural network is employed to predict the concentration of ambient respirable particu-late matter (PM10) and toxic metals observed in the city of Jaipur, India. A feed-forward network with a back-propagation learning algorithm is used to train the neural network the behavior of the data patterns. The meteorological variables of wind speed, wind direction, relative humidity, temperature, and time are taken as input to the network. The results indicate that the network is able to predict concentrations of PM10 and toxic metals quite accurately.
Prediction of Ambient PM10 and Toxic Metals Using Artificial Neural Networks
Chelani, Asha B. (author) / Gajghate, D.G. (author) / Hasan, M.Z. (author)
Journal of the Air & Waste Management Association ; 52 ; 805-810
2002-07-01
6 pages
Article (Journal)
Electronic Resource
Unknown
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