A Fuzzy Time Series Prediction Method Based on Spectral Clustering
| Autor: | Ronghua Chi, Shao-bin Huang, Chun-nan Zhou, Guo-feng Liu |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Fuzzy clustering
Fuzzy classification Neuro-fuzzy Mathematics::General Mathematics business.industry Fuzzy set Pattern recognition Defuzzification ComputingMethodologies_PATTERNRECOGNITION Fuzzy number Fuzzy set operations ComputingMethodologies_GENERAL Artificial intelligence business Membership function Mathematics |
| Zdroj: | DEStech Transactions on Engineering and Technology Research. |
| ISSN: | 2475-885X |
| DOI: | 10.12783/dtetr/ameme2016/5759 |
| Popis: | The accuracy of fuzzy time series prediction method depends on the accuracy of the discourse division and fuzzy relation extraction. Aiming at the main problems in the model, this paper put forward a kind of fuzzy time series prediction method based on spectral clustering using spectral clustering dividing time series discourse and calculate the corresponding fuzzy sets to construct fuzzy time series; At the same time using second-order Markov probability model constructing fuzzy relation in fuzzy time series, and then predict the subsequent numerical. Compared with the traditional fuzzy time series prediction method, this method can improve the accuracy. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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