An artificial neural networks approach on automobile pricing

被引：25

作者：

Iseri, Ali ^{[1
]}

Karlik, Bekir ^{[2
]}

机构：

[1] Fatih Univ, Dept Ind Engn, Istanbul, Turkey

[2] Fatih Univ, Dept Comp Engn, Istanbul, Turkey

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2009年 / 36卷 / 02期

关键词：

Pricing; Artificial neural networks; Automobile; Stepwise linear regression;

D O I：

10.1016/j.eswa.2007.12.059

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The aim of this study to find an automobile pricing model using artificial neural networks (ANN). As commonly known, pricing is it difficult matter for both automobile manufacturers and buyers/sellers. Developing a neural networks based oil 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 oil 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 oil a stable market from their technical and physical properties. (C) 2007 Elsevier Ltd. All rights reserved.

引用

页码：2155 / 2160

页数：6

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