A Novel Approach on Behavior of Sleepy Lizards Based on K-Nearest Neighbor Algorithm
The K-Nearest Neighbor algorithm is one of the commonly used methods for classification in machine learning and computational intelligence. A new research method and its improvement for the sleepy lizards based on the K-Nearest Neighbor algorithm and the traditional social network algorithms are proposed in this chapter. The famous paired living habit of sleepy lizards is verified based on our proposed algorithm. In addition, some common population characteristics of the lizards are also introduced by using the traditional social net work algorithms. Good performance of the experimental results shows efficiency of the new research method.
KeywordsSocial network analysis (SNA) K-Nearest neighbor (KNN) algorithm Sleep lizard Computational intelligence
The authors would like to thank the reviewers for providing very helpful comments and suggestions. The authors would also like to thank for the support from the project named Research on Multiple Description Coding Frames with Watermarking Techniques in Wavelet Domain which belongs to the NSFC (National Natural Science Foundation of China) with the Grant number 61202456.
- 1.Granovetter, M.: Getting a Job: A Study of Contacts and Careers. Harvard University Press, Cambridge (1974)Google Scholar
- 4.Berton, L., de Andrade Lopes, A.: Informativity-based graph : exploring mutual KNN and labeled vertices for semi-supervised learning. In: Fourth International Conference on Computational Aspects of Social Networks (CASoN), pp. 1120–1123, August 2012Google Scholar
- 5.Guo, X., Chu, S.-C., Tang, L.-L., Roddick, J. F., Pan, J.-S.: A research on behavior of sleepy lizards based on KNN algorithm. In: IEEE the 4th Asian Conference on Intelligent Information and Database System (ACIIDS-2012), Taiwan, pp. 109–118, March 2012Google Scholar
- 6.Hwang, W.J., Wen, K.W.: Fast KNN Classification Algorithm Based on Partial Distance Search. IEEE Trans. Comput. 24(7), 750–753 (1975)Google Scholar
- 8.Pan, J.S., Qiao, Y.L., Sun, S.H., A fast k nearest neighbors classification algorithm. IEICE Trans. Fundam. E87-A(4), 961–963 (2004)Google Scholar
- 9.Lu, Z.M., Sun, S.H.: Equal-average equal-variance equal-norm nearest neighbor search algorithm for vector quantization. IEICE Trans. Inf. Syst. 86(3), 660–663 (2003)Google Scholar
- 10.Hassana, G.K., Shaker, K.A., Zou, B.J.: Optimal approach for texture analysis and classification based on wavelet transform and neural network. J. Inf. Hiding Multimedia Sig. Process. 2(1), 33–40 (2011)Google Scholar
- 11.Stephan, T.L., Bashford, J., Kappeler, P.M., Bull, C.M.: Association networks reveal social organization in the sleepy lizard. Anim. Behav. 79(1), 217–225 (2010)Google Scholar
- 12.Stephan, T.L., Kappeler, P.M., Bull, C.M.: Refuge sharing network predicts ectoparasite load in a lizard. Behav. Ecol. Sociobiol. 64(9), 152–160 (2010)Google Scholar