Abstract:

To predict something we need some background study to understand the pattern. Weather forecasting is the practice of predicting the state of the atmosphere for a given location based on different weather parameters. On earth, every phase of human life is influenced by nature. As we cannot avoid the natural changes and conditions, we have chosen to minimize their effect on our lives. Therefore, to achieve this we need to know the weather conditions beforehand, to make things work according to the changes in the environment. 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. Agriculture is the field that is most influenced by the weather. This paper explores the details of this project. Weather forecasts are made by gathering data about the current state of the atmosphere. Accurate weather forecasting has proven to be a challenging task for meteorologists and researchers. Weather information is essential in every facet of life like agriculture, tourism, airport system, mining industry, and power generation. Weather forecasting has now entered the era of Big Data due to the advancement of climate observing systems like satellite meteorological observation and also because of the fast boom in the volume of weather data. So, the traditional computational intelligence models are not adequate to predict the weather accurately. Hence, deep learning-based techniques are employed to process massive datasets that can learn and make predictions more effectively based on past data. The effective implementation of deep learning in various domains has motivated its use in weather forecasting and is a significant development for the weather industry. This paper provides a thorough review of different weather forecasting approaches, along with some publicly available datasets.

Description:

Weather, Weather Predictions, Forecast, Forecasting Models, Weather data, Forecasting methods and applications