Inductive GMDH-Based Approach to Hierarchical Forecasting

被引:0
|
作者
Ivakhnenko, Gregory [1 ]
机构
[1] Bout Res Grp, London, England
关键词
Hierarchical modelling; Multilevel forecasting; GMDH; Harmonic models; Temporal aggregation;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In the paper, the inductive algorithms of hierarchical modelling for long-term forecasting are considered. GMDH algorithms are used to get accurate long-term forecasts on all levels of temporal data. Inductive approach allows to reconcile models and to increase accuracy of forecasting simultaneously on all levels of modelling. The results show that multi-level inductive algorithms can improve quality and extend forecast horizon in comparison with conventional univariate methods used in the hierarchical forecasting.
引用
收藏
页码:448 / 451
页数:4
相关论文
共 50 条
  • [1] A GMDH-based traffic flow forecasting model
    Hong C.
    Journal of Convergence Information Technology, 2010, 5 (02) : 107 - 111
  • [2] On Constructing Ontology of the GMDH-based Inductive Modeling Domain
    Pidnebesna, Halyna
    PROCEEDINGS OF THE 2017 12TH INTERNATIONAL SCIENTIFIC AND TECHNICAL CONFERENCE ON COMPUTER SCIENCES AND INFORMATION TECHNOLOGIES (CSIT 2017), VOL. 1, 2017, : 511 - 513
  • [3] GMDH-based financial forecasting on a hypercube parallel computer
    Water, PR
    Kerckhoffs, EJH
    SIMULATION IN INDUSTRY'99: 11TH EUROPEAN SIMULATION SYMPOSIUM 1999, 1999, : 586 - 596
  • [4] GMDH-based knowledge extraction
    Muller, J.
    Upravlyayushchie Sistemy i Mashiny, 2003, (02): : 13 - 21
  • [5] A GMDH-based fuzzy modeling approach for constructing TS model
    Zhu, Bing
    He, Chang-Zheng
    Liatsis, Panos
    Li, Xiao-Yu
    FUZZY SETS AND SYSTEMS, 2012, 189 (01) : 19 - 29
  • [6] GMDH-based hybrid model for container throughput forecasting: Selective combination forecasting in nonlinear subseries
    Mo, Lili
    Xie, Ling
    Jiang, Xiaoyi
    Teng, Geer
    Xu, Lixiang
    Xiao, Jin
    APPLIED SOFT COMPUTING, 2018, 62 : 478 - 490
  • [7] GMDH-based stock price prediction
    Water, P.R.
    Wibier, S.
    Kerckhoffs, E.J.H.
    Koppelaar, H.
    Neural Network World, 1997, 7 (4-5): : 553 - 563
  • [8] GMDH-Based Semi-Supervised Feature Selection for Electricity Load Classification Forecasting
    Yang, Lintao
    Yang, Honggeng
    Liu, Haitao
    SUSTAINABILITY, 2018, 10 (01)
  • [9] Research on GMDH-based combination forecast
    Rong, Baoyuan
    Wang, Haiyan
    Chen, Zeren
    Xiang, Yilin
    Feng, Chunyu
    Song, Tingting
    International Journal of Advancements in Computing Technology, 2012, 4 (18) : 616 - 623
  • [10] A Novel Approach for Face Recognition Using Fused GMDH-Based Networks
    El-Alfy, El-Sayed
    Baig, Zubair
    Abdel-Aal, Radwan
    INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY, 2018, 15 (03) : 369 - 377