Journal on Communications ›› 2016, Vol. 37 ›› Issue (2): 107-115.doi: 10.11959/j.issn.1000-436x.2016036
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Chun-nan ZHOU,Shao-bin HUANG,Rong-hua CHI,Ya LI,Da-peng LANG
Online:
2016-02-26
Published:
2016-02-26
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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[J]. Journal on Communications, 2016, 37(2): 107-115.
[1] | SONG Q , CHISSOM B S . Fuzzy time series and its models[J]. Fuzzy Sets System, 1993, 54(3): 269-277. |
[2] | SONG Q , CHISSOM B S . Forecasting enrollments with fuzzy time series[J]. Part I Fuzzy Sets System, 1993, 54(1): 1-9. |
[3] | SONG Q , CHISSOM B S . Forecasting enrollments with fuzzy time series[J]. Part II Fuzzy Sets System, 1994, 62(1): 1-8. |
[4] | LEE L W , WANG L H , CHEN S M . Temperature prediction and TAIEX forecasting based on high-order fuzzy logical relationships and genetic simulated annealing techniques[J]. Expert Systems with Applications, 2008(34): 328-336. |
[5] | CHEN S M , HWANG J R . Temperature prediction using fuzzy time series[J]. IEEE Transactions on Systems, Man, Cybernetics-Part B:Cybernetics, 2000, 30(2): 263-275. |
[6] | 王兆霞, 孙雨耕 . 基于模糊神经网络的网络业务量预测研究[J]. 通信学报, 2005, 26(3): 136-140. WANG Z X , SUN Y G . Study of predicting network traffic using fuzzy neural networks[J]. Journal on Communications, 2005, 26(3): 136-140. |
[7] | YU H K . Weighted fuzzy time-series models for TAIEX forecasting[J]. Physical A, 2004(349): 609-624. |
[8] | 张韬, 冯子健 . 模糊时间序列分析在肾综合征出血热发病率预测的应用初探[J]. 中国卫生统计, 2011, 2: 146-150. ZHANG T , FENG Z J . Application of fuzzy time series analysis in in-cidence of hemorrhagic fever with renal syndrome prediction[J]. China Health Statistics, 2011, 2: 146-150. |
[9] | 倪明 . 模糊时间序列预测模型研究及其在污水处理上的应用[D]. 西南石油大学, 2012. NI M . Fuzzy time series forecasting model and its application in wastewater treatment[D]. Southwest Petroleum University, 2012. |
[10] | ALADAG C H , EGRIOGLU E . A high order seasonal fuzzy time series model and application to international tourism demand of turkey[J]. Applications in Engineering and Technology, 2014, 26(1): 295-302. |
[11] | HUARNG K . Effective lengths of intervals to improve forecasting in fuzzy time series[J]. Fuzzy Sets and Systems, 2001, 123(3): 387-394. |
[12] | LI S T , CHEN Y P . A high order seasonal fuzzy time series model and application to international tourism demand of turkey[C]// /The IEEE International Conference on Fuzzy Systems Budapest. Hungary, c2004: 25-29. |
[13] | CHEN S M , HSU C C . A new method to forecast enrollments using fuzzy time series[J]. International Journal of Applied Science and Engineering, 2004, 2(3): 234-244. |
[14] | TRAN T N , WEHRENS R , BUYDENS L . KNN-kernel density-based clustering for high-dimensional multivariate data[J]. Computational Statistics and Data Analysis, 2006, 51(2): 513-525. |
[15] | CHENG C H , CHANG J R , YEH C A . Entropy-based and trapezoid fuzzification-based fuzzy time series approaches for forecasting IT project cost[J]. Technological Forecasting and Social Change, 2006, 73(5): 524-542. |
[16] | HUARNG K , YU T H . Ratio-based lengths of intervals to improve fuzzy time series forecasting[J]. IEEE Transactions on Systems,Man, and Cybernetics-Part B: Cybernetics, 2006, 36(2): 328-340. |
[17] | LEE L W , WANG L H , CHEN S M . Temperature prediction and TAI-FEX forecasting based on fuzzy logical relationships a netic algo-rithms[J]. Expert Systems with Applications, 2007, (33): 539-550. |
[18] | CHENG C H , CHENG G W , WANG J W . Multi-attribute fuzzy time series method based on fuzzy clustering[J]. Expert Systems with Applications, 2008, 34(2): 1235-1242. |
[19] | YOLCU U , EGRIOGLU E , USLU V R . A new approach for determining the length of intervals for fuzzy time series[J]. Applied Soft Computing, 2009, 9(2): 647-651. |
[20] | EGRIOGLU E , ALADAG C H . Fuzzy time series forecasting ith a novel hybrid approach combining fuzzy c-means and neural networks[J]. Expert Systems with Application, 2013, 40(3): 854-857. |
[21] | KHASHEI M . Fuzzy artificial neural network p, d, q model for incomplete financial time series forecasting[J]. Applications in Engineering and Technology, 2014, 26(2): 831-845. |
[22] | CHEN S M , KAO P Y . TAIEX forecasting based on fuzzy ti series, particle swarm optimization techniques and support vec ma-chines[J]. Information Sciences, 2013, 247(15): 62-71. |
[23] | BAS E , USLU V R , YOLCU U . A modified genetic algorithm for forecasting fuzzy time series[J]. Applied Intelligence, 2014, 41(2): 453-463. |
[24] | 曹盼盼, 阎春宁 . 人类通信模式的幂律分布和Zipf定律[J]. 复杂系统与复杂科学, 2009, 6(4): 51-56. CAO P P , YAN C N . The power law and Zipf's law in huma mmu-nication patterns[J]. Complex Systems and Complexity Science, 2009, 6(4): 51-56. |
[25] | CHEN S M , WANG N Y , PAN J S . Forecasting enrollments using automatic clustering techniques and fuzzy logical relationship[J]. Expert Systems with Applications, 2009, 36(8): 11070-11076. |
[26] | CHEN S M , TANUWIJAYA K . Multivariate fuzzy forecasting based on fuzzy time series and automatic clustering techniques[J]. Expert Systems with Applications, 2011, 38(8): 10594-10605. |
[27] | MILLS T C . Time series techniques for economists[J]. Cambridge: Cambridge University Press 1990. |
[28] | LI S T , KUO S C , CHENG Y C , et al. A vector forecastin model for fuzzy time series[J]. Applied Soft Computing, 2011, 11(3): 3125-3134. |
[29] | WANG W , LIU X . Fuzzy forecasting based on automatic cl stering and axiomatic fuzzy set classification[J]. Information Sciences, 2015, 294(294): 78-94. |
[30] | NG A Y , JORDAN M I , WEISS Y . On spectral clustering: analysis and an algorithm[J]. Advances in Neural Information Processing Systems, 2002, 2(8): 849-856. |
[31] | LUXBURG U V . A tutorial on spectral clustering[J]. Statistics and Computing, 2007, 17(4): 395-416. |
[32] | LI M , LI Y C , LENG J X . Powertype functions of prediction error of sea le-vel time series[J]. Entropy, 2015, 17(7): 4809-4837. |
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