A Time Series ANN Approach for Weather Forecasting
نویسندگان
چکیده
Weather forecasting is most challenging problem around the world. There are various reason because of its experimented values in meteorology, but it is also a typical unbiased time series forecasting problem in scientific research. A lots of methods proposed by various scientists. The motive behind research is to predict more accurate. This paper contribute the same using artificial neural network (ANN) and simulated in MATLAB to predict two important weather parameters i.e. maximum and minimum temperature. The model has been trained using past 60 years of real data collected from(1901-1960) and tested over 40 years to forecast maximum and minimum temperature. The results based on mean square error function (MSE) confirm, this model which is based on multilayer perceptron has the potential to successful application to weather forecasting.
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