High-order fuzzy time series self-adaption prediction method based on spectral clustering
A fuzzy time series self-adaption prediction method based on spectral clusterin and data characteristics was proposed. First, based on spectral clustering and the racteristics of data, the number and scope of the discourses was obtained to convert into fuzzy time series self-adaptively. Then, fuzzy...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2016-02-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016036/ |
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| _version_ | 1841539600056582144 |
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| author | Chun-nan ZHOU Shao-bin HUANG Rong-hua CHI Ya LI Da-peng LANG |
| author_facet | Chun-nan ZHOU Shao-bin HUANG Rong-hua CHI Ya LI Da-peng LANG |
| author_sort | Chun-nan ZHOU |
| collection | DOAJ |
| description | A fuzzy time series self-adaption prediction method based on spectral clusterin and data characteristics was proposed. First, based on spectral clustering and the racteristics of data, the number and scope of the discourses was obtained to convert into fuzzy time series self-adaptively. Then, fuzzy relationships based on Markov probability model was presented, and the multi-steps, high-order and steady fuzzy relationship are gotten.Finally, proposed meted obtained the probable fuzzy states, and got its predicted values based on defuzzification methods. Experiments on real-world and synthetic time series data indicate the rationality and effectiveness of the proposed method. |
| format | Article |
| id | doaj-art-a5bfb2617e364b2398fd05f4341f7176 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2016-02-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-a5bfb2617e364b2398fd05f4341f71762025-01-14T06:54:50ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2016-02-013710711559699278High-order fuzzy time series self-adaption prediction method based on spectral clusteringChun-nan ZHOUShao-bin HUANGRong-hua CHIYa LIDa-peng LANGA fuzzy time series self-adaption prediction method based on spectral clusterin and data characteristics was proposed. First, based on spectral clustering and the racteristics of data, the number and scope of the discourses was obtained to convert into fuzzy time series self-adaptively. Then, fuzzy relationships based on Markov probability model was presented, and the multi-steps, high-order and steady fuzzy relationship are gotten.Finally, proposed meted obtained the probable fuzzy states, and got its predicted values based on defuzzification methods. Experiments on real-world and synthetic time series data indicate the rationality and effectiveness of the proposed method.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016036/fuzzy time seriesspectral clusteringdiscourse partitionMarkov probability modelfuzzy relationship |
| spellingShingle | Chun-nan ZHOU Shao-bin HUANG Rong-hua CHI Ya LI Da-peng LANG High-order fuzzy time series self-adaption prediction method based on spectral clustering Tongxin xuebao fuzzy time series spectral clustering discourse partition Markov probability model fuzzy relationship |
| title | High-order fuzzy time series self-adaption prediction method based on spectral clustering |
| title_full | High-order fuzzy time series self-adaption prediction method based on spectral clustering |
| title_fullStr | High-order fuzzy time series self-adaption prediction method based on spectral clustering |
| title_full_unstemmed | High-order fuzzy time series self-adaption prediction method based on spectral clustering |
| title_short | High-order fuzzy time series self-adaption prediction method based on spectral clustering |
| title_sort | high order fuzzy time series self adaption prediction method based on spectral clustering |
| topic | fuzzy time series spectral clustering discourse partition Markov probability model fuzzy relationship |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016036/ |
| work_keys_str_mv | AT chunnanzhou highorderfuzzytimeseriesselfadaptionpredictionmethodbasedonspectralclustering AT shaobinhuang highorderfuzzytimeseriesselfadaptionpredictionmethodbasedonspectralclustering AT ronghuachi highorderfuzzytimeseriesselfadaptionpredictionmethodbasedonspectralclustering AT yali highorderfuzzytimeseriesselfadaptionpredictionmethodbasedonspectralclustering AT dapenglang highorderfuzzytimeseriesselfadaptionpredictionmethodbasedonspectralclustering |