|
[1]
|
Sakurai, Y., Papadimitriou, S. and Faloutsos, C. (2005) Braid: Stream Mining through Group Lag Correlations. Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data, Baltimore, 14-16 June 2005, 599-610. http://dx.doi.org/10.1145/1066157.1066226 [Google Scholar] [CrossRef]
|
|
[2]
|
林子雨, 江弋, 赖永炫, 林琛. 一种新的时间序列延迟相关性分析算法——三点预测探查法[J]. 计算机研究与发展, 2012(12): 2645-2655.
|
|
[3]
|
Yue, D., Zhang, T., Yu, G., et al. (2007) Lag Correlation Analysis Based on Boolean Presentation over Multiple Data Streams. International Conference on Intelligent Systems and Knowledge Engineering. Atlantis Press, Paris.
http://dx.doi.org/10.2991/iske.2007.133 [Google Scholar] [CrossRef]
|
|
[4]
|
Zhang, T., Yue, D., Wang, Y., et al. (2011) A Novel Approach for Mining Multiple Data Streams Based on Lag Correlation. 2011 Chinese Control and Decision Conference (CCDC), Mianyang, 23-25 May 2011, 2377-2382.
http://dx.doi.org/10.1109/CCDC.2011.5968606 [Google Scholar] [CrossRef]
|
|
[5]
|
Fungwacharakorn, W. and Pattara-Atikom, W. (2014) Enhancement of Lag Time Query on Hydrologic Data Using Clipping Technique and Logic-Based Correlation. 2014 11th International Conference on Electrical Engineering/ Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), Nakhon Ratchasima, 14-17 May 2014, 1-6. http://dx.doi.org/10.1109/ECTICon.2014.6839813 [Google Scholar] [CrossRef]
|
|
[6]
|
武红江, 赵军平, 彭勤科, 黄永宣. 基于波动特征的时间序列数据挖掘[J]. 控制与决策, 2007, 22(2): 160-163.
|
|
[7]
|
谢福鼎, 王赫楠, 张永. 一种新的时间序列线性拟合方法[J]. 计算机工程, 2011, 37(22): 250-251+254.
|
|
[8]
|
李海林. 基于动态弯曲的时间序列异步相关性分析[J]. 计算机应用研究, 2014, 31(7): 1976-1979.
|
|
[9]
|
Serra, J. and Arcos, J.L. (2012) A Competitive Measure to Assess the Similarity between Two Time Series. Case- Based Reasoning Research and Development. Springer, Berlin Heidelberg, 414-427.
http://dx.doi.org/10.1007/978-3-642-32986-9_31 [Google Scholar] [CrossRef]
|
|
[10]
|
Stefan, A., Athitsos, V. and Das, G. (2013) The Move-Split-Merge Metric for Time Series. IEEE Transactions on Knowledge and Data Engineering, 25, 1425-1438. http://dx.doi.org/10.1109/TKDE.2012.88 [Google Scholar] [CrossRef]
|
|
[11]
|
Nakamura, T., Taki, K., Nomiya, H., et al. (2013) A Shape-Based Similarity Measure for Time Series Data with Ensemble Learning. Pattern Analysis and Applications, 16, 535-548. http://dx.doi.org/10.1007/s10044-011-0262-6 [Google Scholar] [CrossRef]
|
|
[12]
|
Boucheham, B. (2010) Reduced Data Similarity-Based Matching for Time Series Patterns Alignment. Pattern Recognition Letters, 31, 629-638. http://dx.doi.org/10.1016/j.patrec.2009.11.019 [Google Scholar] [CrossRef]
|
|
[13]
|
Li, H., Guo, C. and Qiu, W. (2011) Similarity Measure Based on Piecewise Linear Approximation and Derivative Dynamic Time Warping for Time Series Mining. Expert Systems with Applications, 38, 14732-14743.
http://dx.doi.org/10.1016/j.eswa.2011.05.007 [Google Scholar] [CrossRef]
|
|
[14]
|
丁永伟, 杨小虎, 陈根才, Kavs, A.J. 基于弧度距离的时间序列相似度量[J]. 电子与信息学报, 2011, 33(1): 122- 128.
|
|
[15]
|
肖瑞, 刘国华. 基于趋势的时间序列相似性度量和聚类研究[J]. 计算机应用研究, 2014, 31(9): 2600-2605.
|
|
[16]
|
Song, Q., Guo, Q., Wang, K., et al. (2014) A Scheme for Mining State Association Rules of Process Object Based on Big Dat. Journal of Computer and Communications, 2, 17-24. http://dx.doi.org/10.4236/jcc.2014.214002 [Google Scholar] [CrossRef]
|