Advances in Data Analysis and Classification

, Volume 11, Issue 4, pp 759–783 | Cite as

A novel method for forecasting time series based on fuzzy logic and visibility graph

  • Rong Zhang
  • Baabak Ashuri
  • Yong Deng
Regular Article


Time series attracts much attention for its remarkable forecasting potential. This paper discusses how fuzzy logic improves accuracy when forecasting time series using visibility graph and presents a novel method to make more accurate predictions. In the proposed method, historical data is firstly converted into a visibility graph. Then, the strategy of link prediction is utilized to preliminarily forecast the future data. Eventually, the future data is revised based on fuzzy logic. To demonstrate the performance, the proposed method is applied to forecast Construction Cost Index, Taiwan Stock Index and student enrollments. The results show that fuzzy logic is able to improve the accuracy by designing appropriate fuzzy rules. In addition, through comparison, it is proved that our method has high flexibility and predictability. It is expected that our work will not only make contributions to the theoretical study of time series forecasting, but also be beneficial to practical areas such as economy and engineering by providing more accurate predictions.


Forecasting Time series Fuzzy logic Visibility graph Link prediction 

Mathematics Subject Classification




The authors greatly appreciate the reviews’ suggestions and the editor’s encouragement. The work is partially supported by National Natural Science Foundation of China (Grant Nos. 61573290, 61503237).


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Institute of Fundamental and Frontier ScienceUniversity of Electronic Science and Technology of ChinaChengduChina
  2. 2.School of Computer and Information ScienceSouthwest UniversityChongqingChina
  3. 3.Brook Byers Institute for Sustainable Systems (BBISS), Economics of Sustainable Built Environment (ESBE) Lab, School of Building Construction and School of Civil & Environmental EngineeringGeorgia Institute of TechnologyAtlantaGeorgia

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