# A Clustering Algorithm for Evolving Data Streams Using Temporal Spatial Hyper Cube
## 3 Methodology
### Developed Algorithms
#### 3.4.4 BOCEDS Micro-Cluster Update
In Proceedings of the 24 th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, New York, NY, USA, 19-23 August 2018. [CrossRef]
* [PERSON] and [PERSON] (2019) [PERSON]; [PERSON] Anomaly Detection in Time Series data using Hierarchical Temporal Memory Model. In Proceedings of the 2019 3 rd International conference on Electronics, Communication and Aerospace Technology (ICECA), Coimbatore, India, 12-14 June 2019; pp. 1287-1292. [CrossRef]
* [PERSON] et al. (2019) [PERSON]; [PERSON] E.; [PERSON] [PERSON] CorrCorr: A feature selection method for multivariate correlation network anomaly detection techniques. _Comput. Secur._**2019**, _83_, 234-245. [CrossRef]
* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON]; [PERSON] DeepAnT: A Deep Learning Approach for Unsupervised Anomaly Detection in Time Series. _IEEE Access_**2019**, \(7\), 1991-2005. [CrossRef]
* [PERSON] et al. (2017) [PERSON]; [PERSON]; [PERSON] Fully online clustering of evolving data streams into arbitrarily shaped clusters. _Inf. Sci._**2017**, _382-383_, 96-114. [CrossRef]
* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON] A buffer-based online clustering for evolving data stream. _Inf. Sci._**2019**, _489_, 113-135. [CrossRef]
* [PERSON] et al. (2016) [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] MuDi-Stream: A multi density clustering algorithm for evolving data stream. _J. Netw. Comput. Appl._**2016**, _59_, 370-385. [CrossRef]
* [PERSON] et al. (2016) [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] A new combinative distance-based assessment (CODAS) method for multi-criteria decision-making. _Econ. Comput. Econ. Cybern. Stud. Res._**2016**, _50_, 25-44. * [PERSON] et al. (2018) [PERSON]; [PERSON]; [PERSON]; [PERSON] Large-scale cyber attacks monitoring using Evolving Cauchy Possibilistic Clustering. _Appl. Soft Comput. J._**2018**, _62_, 592-601. [CrossRef]
* [PERSON] et al. (2018) [PERSON]; [PERSON]; [PERSON]; [PERSON] _Online Clustering for Evolving Data Streams with Online Anomaly Detection_; Springer International Publishing: Cham, Switzerland, 2018; Volume 10938. * [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON] I-CODAS: An improved online data stream clustering in arbitrary shaped clusters. _Eng. Lett._**2019**, _27_, 752-776. * [PERSON] et al. (2019) [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] An Online Incremental Clustering Framework for Real-Time Stream Analytics. In Proceedings of the 2019 18 th IEEE International Conference On Machine Learning And Applications (ICMLA), Boca Raton, FL, USA, 16-19 December 2019; pp. 1480-1485. [CrossRef]
* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON] [PERSON]: Dynamic clustering for tracking evolving environments. _Pattern Recognit._**2019**, _94_, 162-186. [CrossRef]
* [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON]; [PERSON] Online Clustering of Evolving Data Streams Using a Density Grid-Based Method. _IEEE Access_**2020**, \(8\), 166472-166490. [CrossRef]
* [PERSON] and [PERSON] (2021) [PERSON]; [PERSON] An Online Clustering Approach for Evolving Data-Stream Based on Data Point Density. In Proceedings of the International Conference on Emerging Technologies and Intelligent Systems, Al Buraimi, Oman, 25-26 June 2021; pp. 105-115. [[PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Cost-effective and adaptive clustering algorithm for stream processing on cloud system. _Geoinformatica_**2021**, 1-21. [CrossRef]
* [PERSON] et al. (2022) [PERSON]; [PERSON]; [PERSON]; [PERSON] A Systematic Review of Density Grid-Based Clustering for Data Streams. _IEEE Access_**2022**, _10_, 579-596. [CrossRef]
* [PERSON] (2018) [PERSON]; [PERSON] Estimating data stream tendencies to adapt clustering parameters. _Int. J. High Perform. Comput. Netw._**2018**, _11_, 34-44. [CrossRef]
* [PERSON] et al. (2022) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] An irrelevant attributes resistant approach to anomaly detection in high-dimensional space using a deep hypersphere structure. _Appl. Soft Comput._**2022**, _116_, 108301.