IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v128y2019icp203-209.html
   My bibliography  Save this article

Meteorological sequence prediction based on multivariate space-time auto regression model and fractional calculus grey model

Author

Listed:
  • Wang, Li
  • Xie, Yuxin
  • Wang, Xiaoyi
  • Xu, Jiping
  • Zhang, Huiyan
  • Yu, Jiabin
  • Sun, Qian
  • Zhao, Zhiyao

Abstract

Meteorological data is the basis for climate prediction and various scientific research. It is very important to study and prediction meteorological data. At present, the prediction methods for meteorological data are mainly a single intelligent method or a single point time series method based on time series data, which ignoring the interaction between meteorological sites and multiple meteorological factors. In this paper, Meteorological space-time data is decomposed into high frequency component and low frequency component by Hilbert Huang Transform. The high frequency component is modeling and predicting by fractional calculus grey model. The low frequency component is modeling and predicting by multivariate space-time auto regression model. The model verification results show that compared with the existing time series prediction methods, this method can more fully explain the non-stationary and nonlinear dynamic process of multivariate meteorological space-time sequences.

Suggested Citation

  • Wang, Li & Xie, Yuxin & Wang, Xiaoyi & Xu, Jiping & Zhang, Huiyan & Yu, Jiabin & Sun, Qian & Zhao, Zhiyao, 2019. "Meteorological sequence prediction based on multivariate space-time auto regression model and fractional calculus grey model," Chaos, Solitons & Fractals, Elsevier, vol. 128(C), pages 203-209.
    • Handle: RePEc:eee:chsofr:v:128:y:2019:i:c:p:203-209
    DOI: 10.1016/j.chaos.2019.07.056
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096007791930308X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2019.07.056?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yani Wang & Mingyi Du & Lei Zhou & Guoyin Cai & Yongliang Bai, 2019. "A Novel Evaluation Approach of County-Level City Disaster Resilience and Urban Environmental Cleanliness Based on SDG11 and Deqing County’s Situation," Sustainability, MDPI, vol. 11(20), pages 1-13, October.
    2. Wu, Wen-Ze & Zeng, Liang & Liu, Chong & Xie, Wanli & Goh, Mark, 2022. "A time power-based grey model with conformable fractional derivative and its applications," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    3. Fendzi-Donfack, Emmanuel & Kamkou Temgoua, Gildas William & Djoufack, Zacharie Isidore & Kenfack-Jiotsa, Aurélien & Nguenang, Jean Pierre & Nana, Laurent, 2022. "Exotical solitons for an intrinsic fractional circuit using the sine-cosine method," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    4. Zhang, Yonghong & Mao, Shuhua & Kang, Yuxiao & Wen, Jianghui, 2021. "Fractal derivative fractional grey Riccati model and its application," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    5. Luo, Xilin & Duan, Huiming & He, Leiyuhang, 2020. "A Novel Riccati Equation Grey Model And Its Application In Forecasting Clean Energy," Energy, Elsevier, vol. 205(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:128:y:2019:i:c:p:203-209. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.