Prediction of Zika Virus by Multilayer Perceptron Neural Network (MLPNN) Using Cloud
B. Mahalakshmi1, G. Suseendran2

1B. Mahalakshmi, Ph.D, Research Scholar, Department of Computer Science, Vels Institute of Science, Technology & Advanced Studies VISTAS, Chennai (Tamil Nadu), India.
2G. Suseendran, Department of Information Technology, Vels Institute of Science, Technology & Advanced Studies VISTAS, Chennai (Tamil Nadu), India.
Manuscript received on 10 October 2019 | Revised Manuscript received on 19 October 2019 | Manuscript Published on 02 November 2019 | PP: 249-254 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B10410982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1041.0982S1119
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Abstract: Zika virus a mosquito borne flavivirus disease, which is spreading hastily across all over the world. Nearly 95 countries are infected with Zika, Aedes aegypti Mosquitoes is the source of spreading the virus. Microcephaly, myelitis, Guillain – Barre Syndrome and neuropathy are the causes of ZVD. Miscarriages and preterm birth also possible also occur during the time of infection. To overcome an early prediction system is used for detecting the virus using symptoms. The zika dataset is stored in cloud and in our proposed work a Multilayer Perceptron Neural Network classifier used for predicting the Zika virus. The classifier produces accuracy level of 97% the highest accuracy level. Based on the symptoms ZVD is predicted at earlier stage, if they found as infected RNA test will be taken for the concerned person.
Keywords: Zika Virus, MLPNN, Cloud Computing, Microcephaly, Backpropagation.
Scope of the Article: Cloud Computing