D. Aloise, A. Deshpande, P. Hansen, and P. Popat, "NP-hardness of Euclidean sum-of-squares clustering", Mach. Learn., vol. 75, pp. 245-248, 2009.
M. Mahajan, P. Nimbhorkar, and K. Varadarajan, "The planar -means problem is NP-hard", Theor. Comput. Sci., vol. 442, pp. 13-21, 2012.
H. Qi, Y. Liu, and D. Wei, "GPS-Based vehicle moving state recognition method and its applications on dynamic in-car navigation systems In ", 2014 IEEE 12th International Conference on Dependable, Autonomic and Secure Computing 2014, pp. 354-360
M.E. Celebi, H.A. Kingravi, and P.A. Vela, "A comparative study of efficient initialization methods for the k-means clustering algorithm", Expert Syst. Appl., vol. 40, pp. 200-210, 2013.
M.E. Celebi, "Improving the performance of k-means for color quantization", Image Vis. Comput., vol. 29, pp. 260-271, 2011.
D. Arthur, and S. Vassilvitskii, "K-means++: The advantages of careful seeding In ", Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms Philadelphia, PA, USA 2007, pp. 1027-1035.
M.B. Al-Daoud, "A new algorithm for cluster initialization", Inter. J. Comp. Cont. Quant. Info. Eng., vol. 1, pp. 1016-1018, 2007.
S.J. Redmond, and C. Heneghan, "“A method for initialising the K-rmeans clustering algorithm using kd-trees,” Pattern Recogn", Letters, vol. 28, pp. 965-973, 2007.
M.A. Hasan, V. Chaoji, S. Salem, and M.J. Zaki, "Robust partitional clustering by outlier and density insensitive seeding", Pattern Recognit. Lett., vol. 30, pp. 994-1002, 2009.
K.A.A. Nazeer, and M.P. Sebastian, "Improving the accuracy and efficiency of the k-means clustering algorithm In ", World Congress on Engineering, WCE 2009 Hong Kong, China 2009, pp. 308-12
M. Yedla, S.R. Pathakota, and T.M. Srinivasa, "Enhancing K-means clustering algorithm with improved initial centre", Inter. J. Comp. Sci. Info. Technol., vol. 1, pp. 121-125, 2010.
M. Goyal, and S. Kumar, "Improving the initial centroids of k-means clustering algorithm to generalize its applicability", J. Ins. Eng., vol. 95, pp. 345-350, 2014.
M. Erisoglu, N. Calis, and S. Sakallioglu, "A new algorithm for initial cluster centers in k-means algorithm", Pattern Recognit. Lett., vol. 32, pp. 1701-1705, 2011.
W.L. Al-Yaseen, Z.A. Othman, and M.Z.A. Nazri, "Multi-level hybrid support vector machine and extreme learning machine based on modified K-means for intrusion detection system", Expert Syst. Appl., vol. 67, pp. 296-303, 2017.
A. Broder, L. Garcia-Pueyo, V. Josifovski, S. Vassilvitskii, and S. Venkatesan, "Scalable K-Means by Ranked Retrieval In ", Proceedings of the 7th ACM International Conference on Web Search and Data Mining New York, NY, USA 2014, pp. 233-242.
M. Capó, A. Pérez, and J.A. Lozano, "An efficient approximation to the K-means clustering for massive data", Knowl. Base. Syst., vol. 117, pp. 56-69, 2017.
U. Fayyad, and P.S. Bradley, “Method for refining the initial conditions
for clustering with applications to small and large database
clustering”. US6115708A, 2000.
V.V. Phoha, and K.S. Balagani, “Method to indentify anomalous
data using cascaded K-Means clustering and an ID3 decision tree”. US7792770B1, 2010.
H. Qi, X. Di, J. Li, and H. Ma, Improved K-means algorithm and its application to vehicle steering identification. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering., LNICST: Harbin, China, 2018, pp. 378-386.