Pakistan Journal of Biological Sciences1028-88801812-5735Asian Network for Scientific Information10.3923/pjbs.2007.326.334SaberaliS.F. Sadat NooriS.A. KhazaeiJ. HejaziA. 22007102This study shows the ability of Artificial Neural Network (ANN) technology to be used for the prediction of the correlation between common lambsquarters (Chenopodium album L.) population, corn (Zea mays L.) population and planting pattern in different days after planting (as inputs) with common lambsquarters biomass production (as output). The number of patterns used in this study was 60 which were randomly divided into 45 and 15 data sets for training and testing the neural network, respectively. The results showed that a very good performance of the neural network is achieved. Some explanation of the predicted results is given. The multi layer perceptrons with training algorithm of backpropagation (BP) was the best one for creating nonlinear mapping between input and output parameters. 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