التفاصيل البيبلوغرافية
| العنوان: |
Enhanced System for the Prediction of Vehicle Condition. |
| المؤلفون: |
Cloudin, S., Prithiyanga |
| المصدر: |
International Journal of Vehicle Structures & Systems (IJVSS); 2023, Vol. 15 Issue 7, p944-950, 7p |
| مصطلحات موضوعية: |
MACHINE learning, WEB-based user interfaces, AUTOREGRESSIVE models, LOGISTIC regression analysis, BOX-Jenkins forecasting |
| مستخلص: |
The present-day vehicle monitoring systems retrieve real-time data and problem codes from the car using an OBD-II device and provide the user with this data in unprocessed form. A system that is easy to use is necessary to enable users to understand the status of their car on their own, thereby preventing potentially dangerous collisions. The goal of this research is to create an understandable and user-friendly web application that will allow users to keep an eye on the health of their vehicle. The study explores the idea of the Internet of Vehicles (IoV), imagining a network in which various cars can interact with one another. The research attempts to forecast future vehicle conditions based on current data and classify them as "Good", "Moderate", or "Bad" using machine learning models such as Autoregressive Integrated Moving Average and Ordinal Logistic Regression. [ABSTRACT FROM AUTHOR] |
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