Multi-step ahead tourism demand forecasting: The perspective of the learning using privileged information paradigm

被引：0
|
作者：
Sun, Shaolong [1 ]
Li, Mingchen [2 ,3 ]
Wang, Shouyang [2 ,3 ,4 ]
Zhang, Chengyuan [5 ]
机构：
[1] School of Management, Xi'an Jiaotong University, Xi'an,710049, China
[2] Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing,100190, China
[3] School of Economics and Management, University of Chinese Academy of Sciences, Beijing,100190, China
[4] Center for Forecasting Science, Chinese Academy of Sciences, Beijing,100190, China
[5] School of Economics and Management, Xidian University, Xi'an,710126, China
来源：
Expert Systems with Applications | 2022年 / 210卷
关键词：
Machine learning;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 50 条
  • [1] Multi-step ahead tourism demand forecasting: The perspective of the learning using privileged information paradigm
    Sun, Shaolong
    Li, Mingchen
    Wang, Shouyang
    Zhang, Chengyuan
    EXPERT SYSTEMS WITH APPLICATIONS, 2022, 210
  • [2] Multi-step Ahead Urban Water Demand Forecasting Using Deep Learning Models
    Sahoo B.B.
    Panigrahi B.
    Nanda T.
    Tiwari M.K.
    Sankalp S.
    SN Computer Science, 4 (6)
  • [3] IMPROVING MULTI-STEP AHEAD TOURISM DEMAND FORECASTING: A STRATEGY-DRIVEN APPROACH
    Sun, Shaolong
    Du, Zongjuan
    Zhang, Chengyuan
    Wang, Shouyang
    EXPERT SYSTEMS WITH APPLICATIONS, 2022, 210
  • [4] Multi-step ahead forecasting of daily reference evapotranspiration using deep learning
    Ferreira, Lucas Borges
    da Cunha, Fernando Franca
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2020, 178
  • [5] Multi-step ahead prediction of carbon price movement using time-series privileged information
    Tian, Yingjie
    Wen, Haonan
    Fu, Saiji
    EXPERT SYSTEMS WITH APPLICATIONS, 2024, 255
  • [6] Role of Temporal Information for Multi-step Ahead Forecasting of Solar Irradiance
    Fathima, T. A.
    Nedumpozhimana, Vasudevan
    Wu, Jiantao
    Lee, Yee Hui
    DeV, Soumyabrata
    2021 PHOTONICS & ELECTROMAGNETICS RESEARCH SYMPOSIUM (PIERS 2021), 2021, : 2342 - 2346
  • [7] Learning to Rank for Multi-Step Ahead Time-Series Forecasting
    Duan, Jiuding
    Kashima, Hisashi
    IEEE ACCESS, 2021, 9 : 49372 - 49386
  • [8] Multi-Step Ahead Ex-Ante Forecasting of Air Pollutants Using Machine Learning
    Gocheva-Ilieva, Snezhana
    Ivanov, Atanas
    Kulina, Hristina
    Stoimenova-Minova, Maya
    MATHEMATICS, 2023, 11 (07)
  • [9] Parallel Multi-Step Ahead Power Demand Forecasting through NAR Neural Networks
    Bonetto, Riccardo
    Rossi, Michele
    2016 IEEE INTERNATIONAL CONFERENCE ON SMART GRID COMMUNICATIONS (SMARTGRIDCOMM), 2016,
  • [10] Multi-step ahead forecasting of global solar radiation for arid zones using deep learning
    Chandola, Deeksha
    Gupta, Harsh
    Tikkiwal, Vinay Anand
    Bohra, Manoj Kumar
    INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND DATA SCIENCE, 2020, 167 : 626 - 635
12345