Prediction Of Rainfall Using Hybrid Neural Network

M.L.Iswarya, J.Ravivek, M.V.Saikumar, Siva Kumar Pathuri, N.Anbazhaghan, Shaik Razia

In this paper we examine an Information Analytic application for foreseeing Indian storm precipitation and propose a calculation for Decision making utilizing Fuzzy set Theory. We select likely indicators dependent on affiliation decides that have the most noteworthy certainty levels. These qualities are sustained to the condition layer which performs Fuzzification by triangular enrollment capacities with focuses spoke to as the loads into this layer. We get the indicators from nearby conditions in southern India, including mean ocean level weight, wind speed, Humidity, and most extreme and least temperatures. The worldwide condition factors incorporate Sea Surface Temperature, Cloud Fraction, Direction of Wind. The calculation predicts precipitation. We use Hop Field Neural Network which contains n number of completely associated repetitive neurons in the calculation to predict rainstorm precipitation in peninsular India. Utilizing Indian Institute of Tropical Meteorology information, we found the forecast exactness of our proposed system.

Volume 12 | Issue 2

Pages: 1119-1127

DOI: 10.5373/JARDCS/V12I2/S20201143