Advanced Intelligent Predictive Models for Urban Transportation, 1st Edition eBook

$30.00

. The book emphasizes the predictive models of Big Data, Genetic Algorithm, and IoT with a case study.

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About this eTextbook

. The book emphasizes the predictive models of Big Data, Genetic Algorithm, and IoT with a case study. The book illustrates the predictive models with integrated fuel consumption models for smart and safe traveling.

The text is a coordinated amalgamation of research contributions and industrial applications in the field of Intelligent Transportation Systems. The advanced predictive models and research results were achieved with the case studies, deployed in real transportation environments. Features: Provides a smart traffic congestion avoidance system with an integrated fuel consumption model.

Predicts traffic in short-term and regular. This is illustrated with a case study. Efficient Traffic light controller and deviation system in accordance with the traffic scenario.

IoT based Intelligent Transport Systems in a Global perspective. Intelligent Traffic Light Control System and Ambulance Control System. Provides a predictive framework that can handle the traffic on abnormal days, such as weekends, festival holidays.

Bunch of solutions and ideas for smart traffic development in smart cities. This book focuses on advanced predictive models along with offering an efficient solution for smart traffic management system. This book will give a brief idea of the available algorithms/techniques of big data, IoT, and genetic algorithm and guides in developing a solution for smart city applications.

This book will be a complete framework for ITS domain with the advanced concepts of Big Data Analytics, Genetic Algorithm and IoT. This book is primarily aimed at IT professionals. Undergraduates, graduates and researchers in the area of computer science and information technology will also find this book useful.

ISBNs for Advanced Intelligent Predictive Models for Urban Transportation are 9781000555981, 1000555984 and the print ISBNs are 9781032228044, 1032228040. Additional ISBNs include 9781032108513, 9781003217367, 9781000555905.

Publication details

Author: R. Sathiyaraj; A Bharathi; Balamurugan Balusamy
Publisher: Chapman & Hall

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About this eTextbook

Predicts traffic in short-term and regular. This is illustrated with a case study. Efficient Traffic light controller and deviation system in accordance with the traffic scenario.

Publication details

Author: R. Sathiyaraj; A Bharathi; Balamurugan Balusamy
Publisher: Chapman & Hall

What you receive

A licensed digital edition of this title, supplied as PDF or EPUB. The format is set by the publisher, so email us the ISBN before ordering and we will confirm which one it is.
Delivered to the email address on your order as a secure download link, usually within minutes and always within 24 hours of payment.
Download links do not expire and there is no cap on re-downloads. Readable on any computer, tablet or phone, online or offline.
This is a digital edition. Nothing is printed, packed or posted, and there is no delivery charge.