Abstract

In this article, parameters affecting on formation and elimination of hydrocarbons using artificial neural network are considered and a model to predict THC (total hydrocarbon) amount in air using neural network is earned. Also using neural network model and surveying effect of each parameters on THC amount, optimization of offered model is done. The database to get mentioned model consists 1500 samples of current information in two stations of quality control of Tehran city air. Results of using artificial neural network in prediction of THC amount indicate that neural network model is suitable for predicting THC amount. Also to compare improvement of implementing THC prediction model using artificial neural network, a multivariable regression model is used to predict THC amount and its results indicate that MSE is very low when we use artificial neural network.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.