عنوان مقاله [English]
Minimum Temperatures main factor limiting agricultural activities including farming and the gardening which every year the losses and damages that may enter agricultural products. The kknowledge is very important of the occurrence of these temperatures to prevent possible damage inflicted on the products. The various programs that are related to climatology Climatologist try to analysis of one or more climate variable in the past, its reach to laws and models on the basis of status to predict the future. The one way in this field is regression models and artificial neural network components AI which is used today widely modeling and prediction of climatic parameters. In this study as a possible model for predicting of minimum temperatures in Oroomieh Township through these were models studied and analyzed. The variation of average maximum relative humidity, average wind speed, total rainfall, average minimum and maximum temperature of 26 year period (2000-1975) to predicted Minimum temperatures for 5 years (2005-2001) and used was compared with the actual data. For this purpose, facilities and functions available in MATLAB/2010 and SPSS/21 software were made and for every month a network was designed with under 5 percent error, then was paid designed to evaluate the performance of the model by statistical criteria such as the coefficient of determination, root mean square error, mean squares error, mean absolute error, mean percentage and correlation coefficient. The results of the modeling the predicted minimum temperatures is showed that the maximum error models, artificial neural networks, linear and non-linear regression analysis with real data, respectively, 0.85, 3.06 and 3.26 Celsius degrees. The showed remarkable ability of artificial neural network models in predicting minimum temperatures compared with the regression models. The use of these models could be used the temperature of the pre-defined, and the resource management planning and environmental interference, and the results can be seen in the ways of coping with the cold and frost in the fields of resource management fuels, agriculture and agricultural machinery, irrigation systems and water lines, disease, road accidents and other transportation.