Demand Forecasting In Pharmaceutical Industry Using Neuro-Fuzzy Approach

Year 2014, Volume: 2 Issue: 2, 41 - 49, 21.03.2014

Gökçe Candan , M.fatih Taskin , Harun Yazgan

https://doi.org/10.17858/jmisci.06816

Cited By: 13

Abstract

Because of human healthcare, the pharmaceutical industry can be considered as one of the most significant industrial sector. For this reason, demand forecasting in pharmaceutical industry has more complex structure than other sectors. Human factors, seasonal and epidemic diseases, market shares of the competitive products and marketing conditions are considered as main external factors for forecasting pharmaceutical product. Additionally, active ingredients rate is also important factor for forecasting process. The main objective of this study is to predict future periods’ demand from previous sales quantity with considering effects of the external factors by employing a neuro-fuzzy approach. Because of the biases of external effects in Artificial Neural Network (ANN) topology, an ANFIS as neuro fuzzy approach is applied. An example is given to illustrate effectiveness of the approach. 

Keywords

Demand forecasting, Neuro-Fuzzy, Fuzzy Logic, Pharmaceutical Industry

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