The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Long-Term and Short-Term Traffic Forecasting Using Holt-Winters Method: A Comparability Approach With Comparable Data in Multiple Seasons
|
|
Author(s): Aditya R. Raikwar (Kashibai Navale College of Engineering, India), Rahul R. Sadawarte (Kashibai Navale College of Engineering, India), Rishikesh G. More (Kashibai Navale College of Engineering, India), Rutuja S. Gunjal (Kashibai Navale College of Engineering, India), Parikshit N. Mahalle (Kashibai Navale College of Engineering, India)and Poonam N. Railkar (Kashibai Navale College of Engineering, India)
Copyright: 2018
Pages: 15
Source title:
Intelligent Systems: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-5643-5.ch077
Purchase
|
Abstract
The need of faster life has caused the exponential growth in No. of vehicles on streets. The adverse effects include frequent traffic congestion, less time efficiency, unnecessary fuel consumption, pollution, accidents, etc. One of most important solution for resolving these problems is efficient transportation management system. Data science introduces different techniques and tools for overcoming these problems and to improve the data quality and forecasting inferences. The proposed long-term forecasting model can predict numerical values of effective attributes for a particular day on half-hourly basis, at least 24 hours prior to the time of prediction. The proposed forecasting model for short-term analysis will be having access to data as close as 30-minute difference from the time of prediction. Our proposed solution has integrated use of Holt-Winters (HW) method along with comparability schemes for seasonal approach.
Related Content
|
Frederic Andres.
© 2027.
14 pages.
|
|
Kalsoom Safdar, Khairul Najmy Abdul Rani, Mohd Aminudin Jamlos, Siti Julia Rosli, Muhammad Usman Younus, Zanab Safdar.
© 2027.
27 pages.
|
|
Bani Adam, Binastya Anggara Sekti, Muhammad Adi Zacky Zahran.
© 2027.
24 pages.
|
|
Swetha Margaret T. A., Renuka Devi D..
© 2027.
31 pages.
|
|
Maurice Saluschke, Michael Schulz.
© 2027.
30 pages.
|
|
Mirjam Sepesy Maučec, Gregor Donaj.
© 2027.
16 pages.
|
|
Jorge A. Ruiz-Vanoye, Ocotlan Diaz-Parra, Ricardo A. Barrera-Cámara, Alejandro Fuentes-Penna, Francisco R. Trejo-Macotela, Jaime Aguilar-Ortiz, Eric Simancas-Acevedo.
© 2027.
21 pages.
|
|
|