The relation between an enterprise and its customers is orders of goods. No benefit will be gotten if there is no order. In addition, forecast of the number of orders is very important for an enterprise, because the number of orders affects production utility. A sudden large number of orders causes the paucity of materials, parts, and human powers. On the other hand, lack of orders causes the waste of enterprise?s resources. Using case data of a real company, in study applies four approaches, including Moving Average, Exponential Smoothing, Artificial Neural Network, and Fuzzy Neural Network, to forecast the company?s orders of goods. The results indicate that Fuzzy Neural Network approach has the best forecast results.
