Study of the relationship between temperature shelter With soil temperature at different depths In terms of humidity Using neural network Model (Case study: Sari)

Soil temperature is the most important factor in sustainable development and agriculture. These factors are not controllable, but by examining the facts and figures it can be predictable and under control. The aim of this study was to evaluate soil temperature at synoptic stations in Sari, Mazandaran province. The study period is from 2003 to 2014. The database consisted of soil temperature at depths of 5, 10, 20, 30, 50 and 100 cm, dry air temperature, soil moisture and air in the above-mentioned period which is collected by the equipment used in meteorological stations. Neural network method is used to estimate the model. Results showed that soil temperature is directly related to air temperature But deep down near the surface of this dependency has been.and Soil temperature with air humidity has fluctuates. So that up to 50 cm rise but decreased with increasing depth. Soil moisture also examined and The results have shown that this agent is effective in high depths.