Markov Chain Order Estimation to the Weather State of Mosul City by Using Backpropagation Network

The operation of order estimation of a Markov chain to represent the observation chain is an important problem in realistic applications. One method of order estimation depending on intelligence technicality is represented by artificial neural networks . in this research we design an artificial neural network which is the backpropagation error (BPE) .This research treated realistic problem in Markov chain order estimation to the weather state of raining months in Nineveh Governorate ( clearly, cloudy, rainy) , and a special algorithm has been prepared for training the network .We suggest another neural network for backpropagation error which is forecasting the weather state , which is designed depending on the past network after modify it.