International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 182 - Issue 34 |
Published: Dec 2018 |
Authors: Munmun Biswas, Tanni Dhoom, Sayantanu Barua |
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Munmun Biswas, Tanni Dhoom, Sayantanu Barua . Weather Forecast Prediction: An Integrated Approach for Analyzing and Measuring Weather Data. International Journal of Computer Applications. 182, 34 (Dec 2018), 20-24. DOI=10.5120/ijca2018918265
@article{ 10.5120/ijca2018918265, author = { Munmun Biswas,Tanni Dhoom,Sayantanu Barua }, title = { Weather Forecast Prediction: An Integrated Approach for Analyzing and Measuring Weather Data }, journal = { International Journal of Computer Applications }, year = { 2018 }, volume = { 182 }, number = { 34 }, pages = { 20-24 }, doi = { 10.5120/ijca2018918265 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2018 %A Munmun Biswas %A Tanni Dhoom %A Sayantanu Barua %T Weather Forecast Prediction: An Integrated Approach for Analyzing and Measuring Weather Data%T %J International Journal of Computer Applications %V 182 %N 34 %P 20-24 %R 10.5120/ijca2018918265 %I Foundation of Computer Science (FCS), NY, USA
Weather forecasting is the use of science and technology to predict the condition of the weather for a given area. It is one of the most difficult issues the world over. This project aims to estimate the weather by utilizing predictive analysis. For this reason, analysis of various data mining procedures is needed before apply. This paper introduces a classifier approach for prediction of weather condition and shows how Naive Bayes and Chi square algorithm can be utilized for classification purpose. This system is a web application with effective graphical User Interface. User will login to the system utilizing his user ID and password. User will enter some information such as current outlook, temperature, humidity and wind condition. This system will take this parameter and predict weather after analyzing the input information with the information in database. Consequently two basic functions to be specific classification (training) and prediction (testing) will be performed. The outcomes demonstrated that these data mining procedures can be sufficient for weather forecasting.