Crsv Score Dashboard to Predict Car Resale Price using Deep Neural Network

Abstract

With an increasingly flourishing quantity of private cars and the advancement of the used car market, used cars have to become the top priority for buyers. The price of a used car is an important aspect of a successful transaction for both buyers and sellers. However, used car transactions are much more complex than other commodity transactions, as the sale price is influenced not only by the basic features of the car itself, such as brand, power, and structure, but also by the condition of the car, such as mileage and usage time, as well as a lack of presently available methods determining which factors hit the sale price most dramatically. Traditionally, used car price appraisal methods include the replacement cost method, the present value of earnings method, the current market value method, and the liquidation price method. However, the traditional appraisal methods are difficult to select uniform indicators for and overly rely on the subjective judgment of appraisers, which is beyond the limits of online trading in the used car market. The accurate evaluation of used cars should be based on a standardized value evaluation system. As a scientific and effective model, deep residual networks will become an important method of used car value evaluation. This project aims to build a model to predict used cars' reasonable prices based on multiple aspects, including vehicle mileage, year of manufacturing, fuel consumption, transmission, road tax, fuel type, and engine size. An iterative framework LSTM is proposed in this project. First, the relevant data processing is carried out for the initial recognition features. Then, by training the deep residual network, the predicted results are fused with the original features as new features. Finally, the new feature group is input into the iteration framework for training, the iteration is stopped, and the results are output when the performance reaches the highest value. We will be integrated to the web-based application where the user is notified with the status of his product