Weather Forecasting, Data Mining, Neural Integration Networks, Decision Trees.
Abstract
Climate forecasts are an important use of climate and have been one of the problems of science and technology worldwide for the past century. In this paper, we investigate the use of data mining techniques to predict high temperatures, precipitation, evaporation and wind. This was done using the random forest regressors using the decision tree algorithm and the mean of the output of the different different decision tree . A meteorological data model was developed and this was used to train classifier algorithms and the data is being drawn or taken from the country Sweden and the data is from 2000 to half of the 2019 . The performance of these algorithms was compared using standard performance metrics, and the algorithm yielded the best results used to extract the rules for the classification of such climate variables. The Neural Network prediction model has also been developed for the system for forecasting the weather and results in comparison to the actual weather data for the predicted times. The results indicate that if sufficient data are provided, Mining data strategies can be used for climate forecasts and climate studies.
