Time series forecasting based on a multidimensional Taylor network model with clustering of dynamic characteristics-Reference-Cited by-同舟云学术

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Time series forecasting based on a multidimensional Taylor network model with clustering of dynamic characteristics

Published:2021-12-27 Issue: Volume: Page:1-10
ISSN:0160-5682
Container-title:Journal of the Operational Research Society
language:en
Short-container-title:Journal of the Operational Research Society

Author:

Yan Hong-Sen¹²,Zheng Xiao-Yi¹²,Zhou Bo¹²,Zhang Jiao-Jun¹²³

Affiliation:

1. Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Southeast University, Nanjing, PR China

2. School of Automation, Southeast University, Nanjing, PR China

3. Department of Mathematical Sciences, School of Science, Zhejiang Sci-Tech University, Hangzhou, PR China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities of China

Shanghai Aerospace Science and Technology Innovation Foundation

Priority Academic Program Development of Jiangsu Higher Education Institutions

Publisher

Informa UK Limited

Subject

Marketing,Management Science and Operations Research,Strategy and Management,Management Information Systems

Link

https://www.tandfonline.com/doi/pdf/10.1080/01605682.2021.2011627

Reference36 articles.

1. Dynamic System Equivalents: A Survey of Available Techniques

2. Modelling high-tech product life cycles with short-term demand information: a case study

3. Demand forecasting and sharing strategies to reduce fluctuations and the bullwhip effect in supply chains

4. Bayesian forecasting with the Holt–Winters model

5. Neural network approach to forecasting of quasiperiodic financial time series

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1. FORECASTING DEMAND LEVEL USING TIME SERIES AND MACHINE LEARNING UNDER UNCERTAINTY CONDITIONS;INT J IND ENG-THEORY;2023

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