Sales Prediction of Electronic Appliances using a Convergence Model based on Artificial Neural Network and Genetic Algorithm

인공신경망과 유전자 알고리즘 기반의 융합모델을 이용한 가전제품의 판매예측

  • Received : 2015.07.13
  • Accepted : 2015.09.20
  • Published : 2015.09.28


The brand and product awareness of Korean electronics companies in the North American market has grown significantly and North American consumers has been recognized as an innovative technology products good performance of Korean electronics appliances. The consumer need of energy saving has led to a rise in market share because Korean electronics appliances have the excellence in energy saving aspects. The expansion of smartphones and mobile devices and the development of smart grid technology can affect electronics market. Domestic companies are continuously develop new product to provide consumers convenient with a variety of additional features combined consumer products. This study proposes a convergence model for sales prediction of electronic appliances using sales data of A company from the North American market. We develop the convergence model for sales prediction based on based on artificial neural network and genetic algorithm. In addition, we validate the superiority of the proposed convergence model by comparing the prediction performance of traditional prediction models.

북미시장에서 국내 가전업체의 브랜드 및 제품 인지도는 크게 성장했으며 북미 소비자들에게 국내 기업의 제품은 성능이 좋고 혁신적인 기술 제품으로 인식되고 있다. 또한 에너지 절약을 원하는 소비자가 늘어나면서 국내 가전제품의 에너지 절약 측면에서 우수성이 부각됨에 따라 시장점유율이 상승으로 이어지고 있다. 최근 스마트폰과 모바일 기기 시장 확대 및 스마트 그리드 기술 발달의 영향으로 가전제품 시장에도 스마트 열풍이 거세게 몰아치고 있는데, 국내 기업들은 가전제품과 결합된 다양한 부가기능을 통해 소비자 편의를 제공함에 따라 지속적인 제품개발을 하고 있다. 본 연구에서는 지속적인 경쟁우위를 유지하기 위한 방안으로 국내 A사의 북미시장에서의 TV 판매 데이터를 이용하여 북미시장에서의 가전제품 판매예측을 위한 융합모델을 개발하고자 한다. 본 연구에서는 인공신경망과 유전자 알고리즘 기반의 융합모델을 이용한 가전제품의 판매예측을 수행하기로 한다. 추가적으로 본 연구에서는 제안한 융합모델과 기존의 예측모델과의 비교분석을 통해 제안한 융합모델의 우수성을 입증하기로 한다.



Supported by : 상명대학교


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