Open AccessMeteorological Data Analysis using Artificial Neural Networks
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.b1009.1292s19
Subject(s) - artificial neural network , confusion matrix , cloud cover , confusion , environmental science , meteorology , statistics , computer science , mathematics , artificial intelligence , cloud computing , geography , psychology , psychoanalysis , operating system
This paper focuses on weather data analysis for Bangalore urban region(Karnataka,India) over a span of 30 years. The 30 years data is preprocessed to have average monthly temperature, vapor pressure, PET (Potential-Evapo Transpiration), cloud cover, rainfall. These features are considered as factors affecting the rainfall. The correlation between the above mentioned parameters with the monthly rainfall are found using spearman correlation. Artificial Neural Networks (ANN) is used to classify instances as less rain, medium and heavy rain. The results of accuracy, confusion matrix is tabulated. Also the optimal number epochs, number of neurons and number of hidden layers is also identified for the data. The graph of actual output and predicted output is plotted.