TY - JOUR T1 - Preparation of the Autumn Brassica napus Yield Map by Using Perceptron Neural Network, Case Study: Sabzevar Township TT - تهیه نقشه عملکرد محصول کلزای پاییزه با استفاده از شبکه عصبی پرسپترون مطالعه موردی: شهرستان سبزوار JF - geospace JO - geospace VL - 13 IS - 41 UR - http://geographical-space.iau-ahar.ac.ir/article-1-198-en.html Y1 - 2013 SP - 171 EP - 180 KW - Yield estimation KW - Brassica napus KW - Neural Network KW - GIS KW - Sabzevar Township N2 - Brassica napus as an oilseed is a strategic agriculture product in Iran. Knowing the best area for cultivation, helps plan and explore suitable cultivation areas efficiently. At this research, we study 24-Brassica napus farm samples to calculate the actual yields by using GPS set. The independent data are variables introduced such as mean temperature, growing degree-day, mean absolute minimum temperature, mean absolute maximum temperature , mean temperature in sowing time, mean potential evapotranspiration, slope , EC of groundwater, pH of groundwater, and mean relative humidity. We analyzed the consequences of environmental potential on autumn Brassica napus yield using Perceptron neural network by multi-layers structure with 3 hidden layers and feed backward algorithm entered to database and Brassica napus cultivation suitability map was prepared in geographic information system environment. Results show that T-test between actual and prediction values do not have significant difference in 0.05 level. We calculated Pearson correlation coefficient at 0.98, RMSE and MAE. Thus 243 and 101 Kg/h indicate the ability of neural network methods for agricultural product yield predictions. M3 ER -