An Extended Version of the Fuzzy-Euclidean Intelligent Fitness Model (FEIFM) Implementation for Selecting Personal Vehicle
Calvin Chang, Edwin and Ditdit Nugeraha Utama
DOI : 10.3844/jcssp.2019.1123.1132
Journal of Computer Science
Volume 15, Issue 8
Indeed, intelligent model is a sub-domain in computer science that its purposes utilized in numerous pieces of reality. Particularly in case of automotive industry, to select the most appropriate personal vehicle is challenging for the customers. The challenge was taken as a main problem of this study. In this research, the reasonableness is characterized by the customer parameters which portray the customer’s identity. By utilizing the mix technique for fuzzy-logic and Euclidean distance calculation, the customer’s identities are fitted into the personal-vehicle parameters. At long last, the constructed model for choosing personal vehicle plays several customer’s parameters; e.g., age, gender, education, income and job. The model designed thru utilizing the object-oriented methodology. The result of simulation of 66 purchasers and 44 conceivable vehicles are able to propose the most reasonable vehicle for every purchaser. As an extended version, the model successfully delivers the completed scheme due to added parameters and method. It is a truthful contribution provided by this research.
© 2019 Calvin Chang, Edwin and Ditdit Nugeraha Utama. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.