Evaluation on NTM based Predictive Analytics on Rainfall and Flood Disaster Management

Dr. Namratha.V1, Ms.Lakshmi.N.H2

Assistant Professor, Department of Civil Engineering, Vemana Institute of Technology

Assistant Professor, Department of Civil Engineering, Vemana Institute of Technology

Abstract—

In this Research article, we presented a new approach for predicting the flood through the advanced Machine learning Algorithm which is one among the Neural networks class that outperforms itself in best data operations and predictive analytics. This Research article discusses in detail about the prediction of flood occurrences evaluation process. We interpreted the Research with many algorithms that is existing, and the Research work have been dealing with different research works have been inculcated and compared with different Research approaches. On Comparing to the Previous Research its observed that the Neural Turing networks have been performing the prediction of the rainfall and flood-based disasters for the consecutive year counts of 10,15 and

20 with 93.8% accuracy. Here the Research is analyzed with various parameters and comparing it with the other research which is implemented with other machine learning algorithms. Comparing with the previous research the Idea of the research have been described and evaluated with the different evaluation parameters including the number of iterations or Epochs.

Keywords—Rainfall disaster, Machine learning, Neural Turing Networks, Evaluation parameters