Notes on multi-step ahead prediction based on the principle of concatenation

被引:0
|
作者
Rossiter, J.A. [1 ]
机构
[1] Loughborough Univ of Technology
关键词
Adaptive control systems - Algorithms - Forecasting - Mathematical models - Polynomials;
D O I
10.1243/PIME_PROC_1993_207_348_02
中图分类号
学科分类号
摘要
A recent paper by Kaynak in this Journal proposes a more efficient application of generalized predictive control than that of Clarke et al., the most common in the literature. In this technical note, Kaynak's algorithm is compared with two other algorithms of Kouvaritakis and Rossiter already in the literature, and also with the original algorithm of Clarke et al., and it is demonstrated that they all in fact reduce to the same algorithm. Moreover, it is shown that the earlier algorithms are more efficient in the non-adaptive case and that Kaynak's algorithm is not efficient in the adaptive case.
引用
收藏
页码:261 / 263
相关论文
共 50 条
  • [21] Multi-Step Ahead Prediction of the Exchange Rate in Bangladesh by NARX Neural Network
    Hossain, Rumana
    Haque, Mohammed Ikramul
    Syed, Nitu
    4TH INTERNATIONAL CONFERENCE ON MATERIALS ENGINEERING FOR ADVANCED TECHNOLOGIES (ICMEAT 2015), 2015, : 563 - 568
  • [22] Multi-step ahead response time prediction for single server queuing systems
    Amani, Payam
    Kihl, Maria
    Robertsson, Anders
    2011 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (ISCC), 2011,
  • [23] Multi-step ahead prediction for electromechanical device using Multivariate SVM predictor
    Zhang, Zhengkai
    Gu, Lichen
    Zhang, Ping
    MECHATRONICS AND INTELLIGENT MATERIALS III, PTS 1-3, 2013, 706-708 : 878 - 881
  • [24] A Stacked Machine Learning Algorithm for Multi-Step Ahead Prediction of Soil Moisture
    Granata, Francesco
    Di Nunno, Fabio
    Najafzadeh, Mohammad
    Demir, Ibrahim
    HYDROLOGY, 2023, 10 (01)
  • [25] Research on multi-step ahead prediction method for tool wear based on MSTCN-SBiGRU-MHA
    Xue, Jing
    Cheng, Yaonan
    Zhai, Wenjie
    Zhou, Xingwei
    Zhou, Shilong
    ADVANCED ENGINEERING INFORMATICS, 2025, 65
  • [26] Dual attention-based multi-step ahead prediction enhancement for monitoring systems in industrial processes
    An, Nahyeon
    Hong, Seokyoung
    Kim, Yurim
    Cho, Hyungtae
    Lim, Jongkoo
    Moon, Il
    Kim, Junghwan
    APPLIED SOFT COMPUTING, 2023, 147
  • [27] On Multi-Step Look-Ahead Deadlock Prediction for Automated Manufacturing Systems Based on Petri Nets
    Lin, Rongfeng
    Yu, Zhenhua
    Shi, Xiaonan
    Dong, Lihong
    Nasr, Emad Abouel
    IEEE ACCESS, 2020, 8 : 170421 - 170432
  • [28] Probabilistic multi-step ahead streamflow forecast based on deep learning
    Karimanzira, Divas
    Richter, Lucas
    Hilbring, Desiree
    Loedige, Michaela
    Vogl, Jonathan
    AT-AUTOMATISIERUNGSTECHNIK, 2024, 72 (06) : 518 - 527
  • [29] A multi-step decision prediction model based on LightGBM
    Luo, Yuhao
    Xu, Qianfang
    Li, Wenliang
    Jiang, Feng
    Xiao, Bo
    2021 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2021, : 5714 - 5718
  • [30] Modeling of Nonlinear Autoregressive Neural Network for Multi-Step Ahead Air Quality Prediction
    Pasic, Mirza
    Bijelonja, Izet
    Kadric, Edin
    Bajric, Hadis
    TEM JOURNAL-TECHNOLOGY EDUCATION MANAGEMENT INFORMATICS, 2020, 9 (03): : 852 - 861