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Data Coding and Neural Network Arbitration for Feasibility Prediction of Car Marketing

  • Adnan KhashmanEmail author
  • Gunay Sadikoglu
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 896)

Abstract

In this paper, we investigate and develop an intelligent system for predicting the marketing feasibility of cars based on using selected decisive car features and a supervised neural network prediction model. The novelty in our work is firstly using simple yet important car feature indicators that consumers often rely on when making a purchase decision. Secondly, designing and implementing a neural prediction model using a large freely available dataset with 1728 car evaluation instances. Our obtained experimental results suggest that using neural networks can be effectively used in predicting the feasibility of car selling or marketing based on its offered basic vehicle features.

Keywords

Neural networks Prediction Marketing feasibility Car sales 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Final International UniversityKyrenia, Mersin 10Turkey
  2. 2.European Centre for Research and Academic Affairs (ECRAA)Nicosia, Mersin 10Turkey
  3. 3.Department of MarketingNear East UniversityNicosia, Mersin 10Turkey

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