Explaining of Costing new Model Based on Neuro- Fuzzy Time Driven Activity ( Case Study of Hormozgan Gas Company)

Assumed that, Activity-based costing methods, such traditional activity-based costing (ABC) time driven activity based costing (TDABC), to have a linear relationship between cost and activity,but the cost function is linear, always. To solve this problem, researchers used artificial and fuzzy intelligence models. Undoubtedly, the simultaneous combination of artificial and fuzzy intelligence models will lead increased cost accuracy. Therefore, for the first time, in the present study, the TDABC method combined with the neural-fuzzy model (ANFIS) and the case study of Hormozgan Gas Company. For purpose, at first, resources and activities of the cost subject were identified. Then, the relationship between cost items and activities was determined in the cost-activity dependency matrix. Subsequently, the sharing rates in the matrix were replaced and the cost of activities was calculated based on the ABC, IABC, TDABC and TDABC-ANFIS methods. Finally, the costing results were compared with the ABC method based on the mean absolute error magnitude (MAD) method results showed that MAD was 0.74 in IABC, 0.60 in TDABC and TDABC-ANFIS in all 18 designed structures in the range (0.591, 0.213). As a result, costing based on TDABC-ANFIS is more accurate than on ABC, IABC, and TDABC. Also, among the structures designed by TDABC-ANFIS, the Gauss2-4-Logsig structure has the lowest error (0.213). Based on the results, among the studied models, the TDABC-ANFIS model is more accurate due to the nonlinear and fuzzy relationship of costs and activities, so, suggesting to the officials of the companies' financial field to use the new TDABC- model