Deciding if the recorded cost of a pre-owned vehicle is a difficult errand, because of the numerous variables that drive a pre-owned car's cost. The focal point of this venture is creating AI models that can precisely anticipate the cost of a trade-in vehicle dependent on its highlights, to make educated buys. We'll be going to look at changed models and calculations which can anticipate the cost of pre-owned vehicles proficiently. More than 70 million passenger vehicles were shipped in 2016. This represents a significant increase in vehicle production over the past decade. As a result, the secondary market for used cars has grown rapidly in recent years. We'll be noticing various strategies and afterward propose the best-fit model to foresee the cost of pre-owned vehicles. Choosing whether a pre-owned vehicle merits the posted cost when you see postings online can be troublesome. A few components, including mileage, make, model, year, and so forth can impact the real worth of a vehicle. From the point of view of a dealer, it is likewise a quandary to value a pre-owned vehicle properly. In light of existing information, the point is to utilize AI calculations to foster models at anticipating utilized vehicle costs.


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    Titel :

    Artificial Intelligence-Enabled regression model for used car price prediction


    Beteiligte:


    Erscheinungsdatum :

    2023-04-28


    Format / Umfang :

    566376 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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