A Hybrid Short-Term Traffic Flow Prediction Model Based on Singular Spectrum Analysis and Kernel Extreme Learning Machine
Author:
Funder
The Chinese National High Technology Research and Development Program
The National Natural Science Foundation of China
Publisher
Public Library of Science (PLoS)
Subject
Multidisciplinary
Reference64 articles.
1. Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection;S Yang;PloS one,2015
2. Online-SVR for short-term traffic flow prediction under typical and atypical traffic conditions;M Castro-Neto;Expert Systems with Applications,2009
3. A computationally efficient two-stage method for short-term traffic prediction on urban roads;F Guo;Transportation Planning and Technology,2013
4. A two-stage short-term traffic flow prediction method based on AVL and AKNN techniques;M Meng;Journal of Central South University,2015
5. Traffic flow on networks;M Garavello,2006
Cited by 37 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Information Criteria for Signal Extraction Using Singular Spectrum Analysis: White and Red Noise;Algorithms;2024-09-05
2. Short-term traffic flow prediction based on combination of SSA and LSTM;Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024);2024-06-05
3. Enhanced multivariate singular spectrum analysis‐based network traffic forecasting for real time industrial IoT applications;IET Networks;2024-03-12
4. Hourly Long-Term Traffic Volume Prediction with Meteorological Information Using Graph Convolutional Networks;Applied Sciences;2024-03-08
5. Singular spectrum analysis (SSA) based hybrid models for emergency ambulance demand (EAD) time series forecasting;IMA Journal of Management Mathematics;2023-10-03
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3