Please use this identifier to cite or link to this item:
http://nopr.niscpr.res.in/handle/123456789/30656| Title: | CNG exhausts emission modeling: Neural network approach |
| Authors: | Bhandari, Kirti Sekhar, Ch Ravi Rao, A M Gangopadhyay, S |
| Keywords: | ANN;CNG;Exhaust emissions;Regression |
| Issue Date: | Dec-2006 |
| Publisher: | NISCAIR-CSIR, India |
| Abstract: | Traditional statistical regression and Artificial Neural Network (ANN) modeling techniques were applied to assess the emission characteristics of CNG vehicles (cars and three wheelers) to understand the influence of explanatory parameters, like vehicle age, vehicle type and air-fuel ratio on emissions of CO, HC, CO2 and O2. For ANN modeling. multilayer feed-forward neural network with single hidden layer was considered and back propagation algorithm was applied for training. ANN model, ANN models are shown better predictive models than the traditional statistical modeling techniques for predicting the CNG exhaust emissions (CO, HC, CO2, and O2). |
| Page(s): | 1000-1007 |
| ISSN: | 0975-1084 (Online); 0022-4456 (Print) |
| Appears in Collections: | JSIR Vol.65(12) [December 2006] |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| JSIR 65(12) 1000-1007.pdf | 1.23 MB | Adobe PDF | View/Open |
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