| contributor author | Chandrra Sekar | |
| contributor author | B. R. Gurjar | |
| contributor author | C. S. P. Ojha | |
| contributor author | Manish Kumar Goyal | |
| date accessioned | 2017-05-08T22:11:51Z | |
| date available | 2017-05-08T22:11:51Z | |
| date copyright | October 2016 | |
| date issued | 2016 | |
| identifier other | 39446898.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/73262 | |
| description abstract | Air pollution in megacities have caught attention of both researchers and policymakers because of increasing emissions, poor air quality, and potential adverse health impacts on densely inhabited populations. Oxides of nitrogen, particulate matter, carbon monoxide, and hydrocarbons are the major air pollutants of vehicular emissions near major intersections and arterials in megacities. The present study is mainly aimed at predicting | |
| publisher | American Society of Civil Engineers | |
| title | Potential Assessment of Neural Network and Decision Tree Algorithms for Forecasting Ambient PM2.5 and CO Concentrations: Case Study | |
| type | Journal Paper | |
| journal volume | 20 | |
| journal issue | 4 | |
| journal title | Journal of Hazardous, Toxic, and Radioactive Waste | |
| identifier doi | 10.1061/(ASCE)HZ.2153-5515.0000276 | |
| tree | Journal of Hazardous, Toxic, and Radioactive Waste:;2016:;Volume ( 020 ):;issue: 004 | |
| contenttype | Fulltext | |