Potential Assessment of Neural Network and Decision Tree Algorithms for Forecasting Ambient PM2.5 and CO Concentrations: Case Study-Reference-Cited by-同舟云学术

Potential Assessment of Neural Network and Decision Tree Algorithms for Forecasting Ambient PM2.5 and CO Concentrations: Case Study

Published:2016-10 Issue:4 Volume:20 Page:
ISSN:2153-5493
Container-title:Journal of Hazardous, Toxic, and Radioactive Waste
language:en
Short-container-title:J. Hazard. Toxic Radioact. Waste

Author:

Sekar Chandrra¹,Gurjar B. R.²,Ojha C. S. P.²,Goyal Manish Kumar³

Affiliation:

1. Research Scholar, Dept. of Civil Engineering, Indian Institute of Technology, Roorkee 247667, India (corresponding author).

2. Professor, Dept. of Civil Engineering, Indian Institute of Technology, Roorkee 247667, India.

3. Assistant Professor, Dept. of Civil Engineering, Indian Institute of Technology, Guwahati 781039, India.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Waste Management and Disposal,Geotechnical Engineering and Engineering Geology,Water Science and Technology,General Chemical Engineering,Environmental Chemistry,Environmental Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29HZ.2153-5515.0000276

Reference42 articles.

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2. An analysis of ambient air quality conditions over Delhi, India from 2004 to 2009;Biswas J.;Atmos. Clim. Sci.,2011

3. A neural network-based method for short-term predictions of ambient SO2 concentrations in highly polluted industrial areas of complex terrain

4. Levenberg-Marquardt algorithm for Karachi stock exchange share rates forecasting;Burney S. M. A.;World Acad. Sci. Eng. Technol.,2008

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