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Optimization of Deep Neural Networks for Modeling Traffic Data using GPS
GA.Sampath Dakshina Murthy1, Rudra Pratap Das2, T.Karthikeyan3

1A.Sampath Dakshina Murthy, Department of Electronics and Communication Engineering, Vignan’s Institute of Information Technology, Visakhapatnam, (Andhra Pradesh), India.
2Rudra Pratap Das, Department of Electronics and Communication Engineering, Vignan’s Institute of Information Technology, Visakhapatnam, (Andhra Pradesh), India.
3T.Karthikeyan, Department of Electronics and Communication Engineering, Vignan’s Institute of Information Technology, Visakhapatnam, (Andhra Pradesh), India.

Manuscript received on 23 March 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 March 2019 | PP: 730-735 | Volume-7 Issue-6, March 2019 | Retrieval Number: F2715037619/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: As accident is increasing continually.GPS created traffic data need to optimal .Deep neural networks having more number of hidden layers are the rest portable to solution .Selecting proper DNNs the main objective . By trial and error proper the selective of DNN has been achieved for optimization of traffic data.
Keywords: Back propagation, Neural network, Deep neural network, Recurrent neural networks.
Scope of the Article: Foundations of Communication Networks