Intelligent prediction of traffic volume distribution

QR Code

Intelligent prediction of traffic volume distribution

Traffic issues become one of the most important problems these days because of the life style of human. Therefore, paying more attention to this field seems to be essential. Distributions of traffic volume on urban roads is often described by some statistical models, which are based on probability a...

Full description

Bibliographic Details
Main Authors:	Zamani, Seyed Ali, Mahmud, Ahmad Rodzi, Jahanshiri, Ebrahim, Hussien, Rabie Ali, Karimadini, Mohammad
Format:	Conference or Workshop Item
Language:	English
Published:	2005
Online Access:	http://psasir.upm.edu.my/id/eprint/39007/ http://psasir.upm.edu.my/id/eprint/39007/1/39007.pdf

Similar Items

Comparative Evaluation Of Three Methods For Predicting Traffic Volume
by: Zaman, Seyed Ali
Published: (2008)

Predictive intelligence for a rail traffic management system
by: Roberts, Simon, et al.
Published: (2017)

Statistical evaluation of traffic survey data to relate peak hour volume to daily traffic volume / Mohd Helmizam Kamaruddin
by: Kamaruddin, Mohd Helmizam
Published: (2006)

Traffic Volume Prediction With Segment-Based Regression Kriging and its Implementation in Assessing the Impact of Heavy Vehicles
by: Song, Y., et al.
Published: (2018)

An intelligent traffic management system.
by: Khatun, Sabira, et al.
Published: (2008)

Comparison between specifications of linear regression and spatial-temporal autoregressive models in mass appraisal valuation for single storey residential property
by: Jahanshiri, Ebrahim
Published: (2013)

Gis-Based Soil Sampling Methods for Precision Farming of Rice
by: Jahanshiri, Ebrahim
Published: (2006)

Prediction of Short-term Traffic Variables using Intelligent Swarm-based Neural Networks
by: Chan, Kit, et al.
Published: (2012)

A review of Traffic State Prediction (TSP) methods in Intelligent Transportation Systems (ITS)
by: Ahanin, Fatemeh, et al.
Published: (2023)

Accident prediction based on integrated design consistency with the lower number of vehicles/traffic volumes (due to health disaster/covid-19)
by: Prasetijo, Joewono, et al.
Published: (2020)

Effect of traffic volume and shoulder width towards crash cases at jalan Kuantan bypass
by: Norazlina, Ahmad Tajuddin
Published: (2018)

An intelligent system to enhance traffic safety analysis
by: Gregoriades, A., et al.
Published: (2011)

A theoretical review on the effects of road hump on traffic volume, speed and noise in residential areas
by: Ahmad Sofi, Siti Syazwani, et al.
Published: (2017)

Development of a Crisp Fuzzy-Like Controller Using Formula-Based and Vectorized Approaches
by: Mohammad, Karimadini
Published: (2006)

Air pollution study of vehicles emission in high volume traffic: Selangor, Malaysia as a case study
by: Ahmad Shuhaili, Ahmad Fadzil, et al.
Published: (2013)

Intelligent Traffic Control (i-TC) for Road Construction
by: Mohd Nizam, Nurul Nazira, et al.
Published: (2020)

Intelligent Dynamic Traffic Light Sequence Using RFID
by: Al-Khateeb, Khalid A. Saeed, et al.
Published: (2008)

Intelligent Traffic Information System for Klang Valley, Malaysia
by: Patrick Soh, Chin-Hooi, et al.
Published: (2008)

Development of Intelligent Distributed Temperature Monitoring System
by: Ahmed Ali, Abduasslam
Published: (2001)

The traffic volume and Level of Service (LOS) of Universiti Putra Malaysia (UPM) Serdang campus main access
by: Ponrahono, Zakiah, et al.
Published: (2019)

Data acquisition process for intelligent traffic light using vision sensor
by: Mohammad S., Hassan, et al.
Published: (2012)

Control and prediction of traffic crashes in the residential streets in Iraq using the expert system
by: Mohammed, Ali Ahmed
Published: (2022)

Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering
by: Davari, Atefeh, et al.
Published: (2011)

Cluttered traffic distribution in LoRa LPWAN
by: Zainal, Nur Aishah, et al.
Published: (2018)

Design of intelligent traffic controlling system using RF transponder
by: Ramalingam, Mritha, et al.
Published: (2018)

Predictive modeling and mapping of Malayan sun bear (Helarctos malayanus) distribution using maximum entropy
by: Nazeri, Mona, et al.
Published: (2012)

Prediction and reduction of traffic pollution in urban areas
by: Bostock, Adam K.
Published: (1994)

Network and traffic engineering in emerging distributed computing applications
by: Abawajy, Jemal H., et al.
Published: (2013)

Traffic noise prediction in bandar mahkota cheras using calculation of road traffic noise (CORTN)
by: Gan, Yuyun
Published: (2023)

Intelligent traffic sign recognition system for autonomous vehicle navigation (ITSRS)
by: Law, Jia Swee
Published: (2018)

Design and implementation of an intelligent fuzzy VLSI chip for traffic control application
by: Islam, , Shabiu, et al.
Published: (2006)

A theoretical overview on effects of road humps on traffic speed, noise and volume in improving residential living environment
by: Bachok, Khairun Sarah Radhiah, et al.
Published: (2015)

Evaluating the effects of road hump on traffic volume and noise level at Taman Keramat residential area, Kuala Lumpur
by: Rosli, Nur Shazwani, et al.
Published: (2013)

Analysis of real time video traffic for enhanced distributed channel access over WLAN
by: Jama, Abdirisaq Mohammed, et al.
Published: (2013)

Predicting the fraud volume in the advent of internet enabled handheld devices
by: Zammarah, Nuha Abdullah, et al.
Published: (2015)

An analytical model to predict the volume of sand during drilling and production
by: Gholami, Raoof, et al.
Published: (2016)

Comparison of intelligent and statistical clustering approaches to predicting total organic carbon using intelligent systems
by: Kadkhodaie, Ali, et al.
Published: (2012)

Severity prediction of traffic accidents with recurrent neural networks
by: Sameen, Maher Ibrahim, et al.
Published: (2017)

Applications of deep learning in severity prediction of traffic accidents
by: Sameen, Maher Ibrahim, et al.
Published: (2017)

Severity prediction of traffic accidents with recurrent neural networks
by: Sameen, Maher Ibrahim, et al.
Published: (2017)