التنبؤ عن الحالات المطرية في مدينة الموصل

Abstract EN

This paper addresses the important problem of prediction of the daily rainfall.

The rainfall situation is modeled as a Markov chain of four states: the lack of rain, light rain, moderate rain, and heavy rain.

After the presentation of the issue of prediction in general terms, two methods are suggested to predict the next rain situations by relying on the information that the real cases providevo.

Two algorithms are suggested for prediction; the first algorithm relies mainly on the matrix of transition, and can be used to find predictors for any order of Markov chain, the second algorithm, the autoregressive models.

These algorithms are applied on the time series of daily rain falling on the City of Mosul, after modeling this time series as a Markov chain of four states.

Linear and non-linear autoregressive models are fitted.

It is clear from the application of these two algorithms that they give reasonable predictors terms of ease of use.