The Journal of the Korea institute of electronic communication sciences (한국전자통신학회논문지)

Korea Institute of Electronic Communication Science (한국전자통신학회)
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A Study for Sales and Demand Forecasting Model Using Wavelet Neural Networks

웨이블렛 신경회로망을 이용한 상품 수요 예측 모형에 관한 연구

  • 이재현 (동명대학교 자율전공학부)
  • Received : 2013.10.25
  • Accepted : 2014.01.13
  • Published : 2014.01.31
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Abstract

In this paper, we develop a fashion products demand forecasting algorithm using ARIMA model and Wavelet Neural Networks model. To show effectiveness of the proposed method, we analyzed characteristics of time-series data collected in "H" company during 2008-2012 and then performed the proposed method through various analyses. As noted in experimental results, the performance of three types model such as ARIMA, Wavelet Neural Networks and ARIMA + Wavelet Neural Networks show 5.179%, 4.553%, and 4.448.% with respect to MAPE(Mean Absolute Percentage Error), respectively. Thus, it is noted that the proposed method can be used to predict fashion products demand for efficient of operation.

본 논문에서는 패션 상품 수요 예측을 위하여 ARIMA 모형과 웨이블렛 신경회로망 모형을 결합한 상품 수요 예측 알고리즘을 개발하였다. 제시된 방법을 검증하기 위하여 2008년에서 2012년까지의 H사의 패션 상품 데이터를 바탕으로 다양한 알고리즘을 축하고 제안한 방법의 정확도를 분석하였다. 실험 결과 ARIMA 모형은 MAPE가 5.179%, 웨이블렛 신경회로망은 4.553%, 제안한 ARIMA + 웨이블렛 신경회로망 모형은 4.448%로 나타나 성능이 우수한 것으로 나타났다. 따라서 제안된 방법을 사용할 경우 패션 상품 수요 예측을 위해 유용하게 활용할 수 있음을 보였다.

Keywords

References

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