Demand Forecasting In Pharmaceutical Industry Using Neuro-Fuzzy Approach

Cilt: 2 Sayı: 2 21 Mart 2014
PDF İndir
EN

Demand Forecasting In Pharmaceutical Industry Using Neuro-Fuzzy Approach

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

Kaynakça

  1. Abdollahzade, M., Miranian, A. & Faraji, S. (2012), Application of emotional learning fuzzy inference systems and locally linear neuro-fuzzy models for prediction and simulation in dynamic systems , FUZZ IEEE , WCCI, 2012 IEEE World Congress On Computational Intelligence
  2. Abraham, A. & Nath, B. (2001), A neuro-fuzzy approach for modelling electricity demand in Victoria, Applied Soft Computing, 1, 2, 127–138
  3. Alizadeh, M., Jolai, F., Aminnayer, M. & Rada, R. (2012), Comparison of different input selection algorithms in neuro-fuzzy modeling, Expert Systems with Applications, 39, 1536–154
  4. Babuška, R., & Verbruggen, H. (2003), Neuro-fuzzy methods for nonlinear system identification, Annual
  5. Reviews in Control, 27, 73–85 Caner, M. & Akarslan, E. (2009), Estimation of specific energy factor in marble cutting process using ANFIS and ANN, Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 15, 2, 221-226.
  6. Craig, A. & Malek, M. (1995), Market structure and conduct in the pharmaceutical industry, Phormac. Ther. 301 337, 0163-7258/95
  7. Confessore, G., Fabiano, M. & Liotta, G. (2011), A network flow based heuristic approach for optimising
  8. AGV movements, Journal of Intelligent Manufacturing , DOI 1007/s10845-011-0612-7

Ayrıntılar

Birincil Dil

İngilizce

Konular

-

Bölüm

-

Yayımlanma Tarihi

21 Mart 2014

Gönderilme Tarihi

25 Mart 2014

Kabul Tarihi

-

Yayımlandığı Sayı

Yıl 2014 Cilt: 2 Sayı: 2

Kaynak Göster

APA
Candan, G., Taskin, M., & Yazgan, H. (2014). Demand Forecasting In Pharmaceutical Industry Using Neuro-Fuzzy Approach. Journal of Management and Information Science, 2(2), 41-49. https://doi.org/10.17858/jmisci.06816
AMA
1.Candan G, Taskin M, Yazgan H. Demand Forecasting In Pharmaceutical Industry Using Neuro-Fuzzy Approach. JMISCI. 2014;2(2):41-49. doi:10.17858/jmisci.06816
Chicago
Candan, Gökçe, M.fatih Taskin, ve Harun Yazgan. 2014. “Demand Forecasting In Pharmaceutical Industry Using Neuro-Fuzzy Approach”. Journal of Management and Information Science 2 (2): 41-49. https://doi.org/10.17858/jmisci.06816.
EndNote
Candan G, Taskin M, Yazgan H (01 Mart 2014) Demand Forecasting In Pharmaceutical Industry Using Neuro-Fuzzy Approach. Journal of Management and Information Science 2 2 41–49.
IEEE
[1]G. Candan, M. Taskin, ve H. Yazgan, “Demand Forecasting In Pharmaceutical Industry Using Neuro-Fuzzy Approach”, JMISCI, c. 2, sy 2, ss. 41–49, Mar. 2014, doi: 10.17858/jmisci.06816.
ISNAD
Candan, Gökçe - Taskin, M.fatih - Yazgan, Harun. “Demand Forecasting In Pharmaceutical Industry Using Neuro-Fuzzy Approach”. Journal of Management and Information Science 2/2 (01 Mart 2014): 41-49. https://doi.org/10.17858/jmisci.06816.
JAMA
1.Candan G, Taskin M, Yazgan H. Demand Forecasting In Pharmaceutical Industry Using Neuro-Fuzzy Approach. JMISCI. 2014;2:41–49.
MLA
Candan, Gökçe, vd. “Demand Forecasting In Pharmaceutical Industry Using Neuro-Fuzzy Approach”. Journal of Management and Information Science, c. 2, sy 2, Mart 2014, ss. 41-49, doi:10.17858/jmisci.06816.
Vancouver
1.Gökçe Candan, M.fatih Taskin, Harun Yazgan. Demand Forecasting In Pharmaceutical Industry Using Neuro-Fuzzy Approach. JMISCI. 01 Mart 2014;2(2):41-9. doi:10.17858/jmisci.06816

Cited By