Gross Domestic Product (GDP) is the total pecuniary or mart value of all final commodity and services that are produced within country's borders in a given time. We choose GDP to predict in Iraq since 2000 to 2018.The state and governments rely on GDP to help shape policy or decide how much public spending is affordable. Combining grey regression is a modern statistical technique of modeling, using this type of model is related to its highly accuracy therefor, in this study we used combined grey regression model to predict the gross domestic production of Iraq because it gives less Mse than grey or regression models alone which is equal to 1.3165 and estimated parameter of grey C1, regression C2 are equals to (2.9 and 0.205) respectively and the intercept C3 is equal to 1.8569 the outcome showed that the new model could attain preferable predicting result contrasted with different predicting methods.

Electric energy is accounted as one of the major goods in human life, and also have a great role in progressing and developing the several sectors as economics, manufactures and any other sector related to daily use. In this study the monthly demand of electricity in Sulaimani governorate have been used, the main goal of the study is to choose appropriate model to forecast the monthly demand of electric in Sulaimani governorate for 12 months in 2020, the analyzing,results and comparison shows that FSARIMA(0,0,0)x(2,1,0) 4 is appropriate model

The development of using location analysis in all aspects of life encouraged us to use it in this paper for analyzing weather in some Kurdistan regions which are (Sulaimaniyah, Erbil and Duhok) based on the data recorded by the devices placed in 27 different areas which had been recording the climate for all months during 2015. Moran test is used to check spatial dependency in a data and Spatial autoregressive model (SAR), spatial error model (SEM) is created also Lagrange test used to select the significant and alternative spatial model between (SAR and SEM). Different criteria or measures like (R2adj, RMSE, MAPE, AICc) are used for finding the best fit model also for all of them used (rook, bishop and queen) matrixes to specify the spatial correlation. The important result in the practical part shows that SAR model for queen and rook matrixes is significant while SEM model is not