Volume 2, Issue 3, December 2009, Pages 277 - 287
A Hybrid Model for Forecasting Sales in Turkish Paint Industry
Available Online 1 December 2009.
- https://doi.org/10.2991/ijcis.2009.2.3.9How to use a DOI?
- Sales forecasting is important for facilitating effective and efficient allocation of scarce resources. However, how to best model and forecast sales has been a long-standing issue. There is no best forecasting method that is applicable in all circumstances. Therefore, confidence in the accuracy of sales forecasts is achieved by corroborating the results using two or more methods. This paper proposes a hybrid forecasting model that uses an artificial intelligence method (AI) with multiple linear regression (MLR) to predict product sales for the largest Turkish paint producer. In the hybrid model, three different AI methods, fuzzy rule-based system (FRBS), artificial neural network (ANN) and adaptive neuro fuzzy network (ANFIS), are used and compared to each other. The results indicate that FRBS yields better forecasting accuracy in terms of root mean squared error (RMSE) and mean absolute percentage error (MAPE).
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - Alp Ustundag PY - 2009 DA - 2009/12 TI - A Hybrid Model for Forecasting Sales in Turkish Paint Industry JO - International Journal of Computational Intelligence Systems SP - 277 EP - 287 VL - 2 IS - 3 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.2009.2.3.9 DO - https://doi.org/10.2991/ijcis.2009.2.3.9 ID - Ustundag2009 ER -