Development of Dust Concentration Model using Artificial Neural Networks
K.V. Nagesha1, Garimella Raghu Chandra2

1K.V. Nagesha, Sr. Assistant Professor, Department of Mechanical Engineering, Madanapalle Institute of Technology & Science, Madanapalle (Andhra Pradesh), India.

2Garimella Raghu Chandra, Associate Professor, Department of Electrical and Electronics Engineering, Methodist College of Engineering and Technology, Hyderabad (Telangana), India. 

Manuscript received on 04 October 2019 | Revised Manuscript received on 18 October 2019 | Manuscript Published on 26 December 2019 | PP: 81-84 | Volume-8 Issue-12S October 2019 | Retrieval Number: L102510812S19/2019©BEIESP | DOI: 10.35940/ijitee.L1025.10812S19

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Abstract: The Minerals extraction from the earth in various open cast mines virtually leads to an enormous amount of dust is releasing to environment. Due to dust dispersed in to atmospheric, various problems occur like health related problems, vegetation problems and chances of accidents of heavy weight moving vehicles on the road. To get permission from EIA (Environmental Impact Assessment) for extending projects and maintaining the green belt environment surrounding of mine models are necessary to determine particulate matters (PM) in the environment. To predict dust emission and concentration values from blasting activity, Artificial Neural Network (ANN) method is used. To train network ‘Trainlm’ algorithm is used, the coefficient of determination value for emission model is 0.99 and for concentration model 0.97 respectively. The ‘Trainlm’ algorithm is the suitable method for predicting the dust emission values and concentration values produce by blasting activity.

Keywords: Model Artificial Neural Networks Development Environment.
Scope of the Article: Artificial Intelligence