An artificial neural networks approach on automobile pricing

  • Authors:
  • Ali İşeri;Bekir Karlık

  • Affiliations:
  • Department of Industrial Engineering, Fatih University, İstanbul, Turkey;Department of Computer Engineering, Fatih University, İstanbul, Turkey

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2009

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Abstract

The aim of this study is to find an automobile pricing model using artificial neural networks (ANN). As commonly known, pricing is a difficult matter for both automobile manufacturers and buyers/sellers. Developing a neural networks based on the technical properties of automobiles will allow both groups to price autos with great ease. However, in this study there are two basic assumptions. The first is that supply and demand are in equilibrium and they have no positive or negative effect on pricing. Alfred Marshall [Alfred Marshall. (1920). Principles of economics (Vol. 9). Macmillan] describes how the price and availability of goods and services are related to consumer demand in competitive markets in the Law of supply and demand. The second is that our data set represents the whole market since we will determine market prices of other automobiles according to the network that is trained by this dataset. Proposed novel model estimates prices of automobiles on a stable market from their technical and physical properties.