Computational Intelligence For Data Analysis

Intelligent Transportation Systems-based Behavior Characteristics Classification

Author(s): B.M.S. Rani, E. Laxmi Lydia* and G. Jose Moses

Pp: 16-31 (16)

DOI: 10.2174/9781681089430121010004

* (Excluding Mailing and Handling)

Abstract

Smart vehicle frames have many special uses and frameworks designed to improve road safety and productivity. We are experiencing rapid advances in advanced Inter Vehicular Communication (IVC) designed by Intelligent Transportation Systems (ITS) to allow the collection, evaluation, and dissemination of applicable data. These frameworks allow you to screen, monitor, and control different parts of the road. The main research to regulate the behavior of the driver is focused on two issues: the formation of identifiable patterns in the test and the grouping of the characteristics of the driver's behavior. In this research proposal, we will have a layout of a Rule-Based Fuzzy Polynomial Neural Networks system based on their behavior in different profiles. Given our reproductive system, we have had the opportunity to speak accurately with the control model, but the main probability models show that the observer rating works relatively well with the sophisticated models.


Keywords: Inter Vehicular Communication, Intelligent Transportation Systems, Rule-Based Fuzzy Polynomial Neural Networks.

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