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Title |
A Survey on Used Vehicle Price Estimation Systems using Artificial Intelligence Methods |
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Author |
Thuraya Alnajim, Nouf Alshahrani, and Omar Asiri |
| Citation |
Vol. 25 No. 1 pp. 168-174 |
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Abstract |
Recently, the market of used car sales has been growing very fast in the Kingdom of Saudi Arabia, due to the high price of new cars that are not affordable by most people. Several Ecommerce websites offer third-party services between the buyers and sellers in the market of used cars. However, it is very helpful to have a previous information about the correct vehicle price for many buyers and sellers before making any decision of selling or buying a used car. Therefore, there is a great demand to develop an accurate vehicle price estimation system through the employment of Machine Learning and Deep Learning techniques. However, there are a large number of significant factors that affect the vehicle price, which make the vehicle price estimation is a difficult task. In general, the standard regression methods might not be efficient for high dimensional data. This paper aims to investigate the recent developed vehicle price estimation systems that are based on the employment of machine learning and deep learning techniques. The recent developed systems are discussed and criticized in details. In addition, we present a set of evaluation metrics to assess the efficiency of any vehicle price prediction system. |
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Keywords |
Vehicle price estimation, machine learning, deep learning, survey. |
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