Protected Combination Of Artificial Neural Network With Wireless Sensor Networks
Pardeep Kumar1, Udayabhanu N P G Raju2
1Dr.Pardeep Kumar, Department of CSE , Vignan Institute of Technology and Science, Hyderabad (Telangana), India.
2Dr. Udayabhanu N P G Raju, Department of CSE , Vignan Institute of Technology and Science, Hyderabad (Telangana), India.
Manuscript received on 18 April 2019 | Revised Manuscript received on 25 April 2019 | Manuscript published on 30 April 2019 | PP: 8-12 | Volume-8 Issue-4, April 2019 | Retrieval Number: D6315048419/19©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: WSN offers a down to earth arrangement of conveyed detecting, preparing, communication and control while ANN’s self-adaptively and nonlinear mapping capacity make it progressively invaluable in displaying nonlinear framework or framework with obscure dynamics. We feel that the blend of WSN and ANN can be an incredible demonstrating arrangement. First, a trainable ANN demonstrate assembled itself from test information, subsequently, adequate information sources are important to acquire a precise ANN show. The rich sensor information from WSN consequently can be utilized in preparing the ANN. Likewise, WSN information based ANN displaying has high down to earth esteems: the conduct of certain framework is exceptionally perplexing and hard to examine, particularly when numerous nonlinear and time-differing impacts are available.
Keywords: ANN, Malicious Traffic Flow, Energy Consumption, WSN.
Scope of the Article: WSN