[1] 刘琳岚, 许江波, 陈宇斌, 等. 基于超限学习机的WSNs链路质量评估方法[J]. 北京邮电大学学报, 2018, 41(1):134-138. Liu Linlan, Xu Jiangbo, Chen Yubin, et al. A link quali-ty estimation method for WSNs based on extreme learning machine[J]. Journal of Beijing University of Posts and Telecommunications, 2018, 41(1):134-138. [2] Zhao Jumin, Li Dengao, Wen Haibin, et al. Load balanced and efficient data collection protocol for wireless sensor networks[J]. International Journal of High Performance Computing and Networking, 2017, 10(6):463-473. [3] Zeng Bing, Jiang Bin, Cao Xiong, et al. A delay-constraint routing metric based on ETX for RPL[J]. Revista de la Facultad de Ingenieria, 2017, 32(1):873-884. [4] Cerpa A, Wong J L, Potkonjak M, et al. Temporal pro-perties of low power wireless links:modeling and implications on multi-hop routing[C]//International Symposium on Mobile Ad Hoc Networking and Computing. Florence:ACM Press, 2005:414-425. [5] Lowrance C J, Lauf A P, Kantardzic M. A fuzzy-based machine learning model for robot prediction of link quality[C]//IEEE Symposium Series on Computational Intelligence. Athens:IEEE Press, 2016:1-8. [6] Da Costa V G T, De Leon Ferreira A C P, Junior S B. Strict very fast decision tree:a memory conservative algorithm for data stream mining[J]. Pattern Recognition Letters, 2018, 116:22-28. [7] Manapragada C, Webb G I, Salehi M. Extremely fast decision tree[C]//International Conference on Knowledge Discovery & Data Mining. London:ACM Press, 2018:1953-1962. [8] Benllarch M, El Hadaj S, Benhaddi M. Improve extremely fast decision tree performance through training dataset size for early prediction of heart diseases[C]//International Conference on Systems of Collaboration Big Data, Internet of Things & Security. Casablanca:IEEE Press, 2019:1-5. [9] Khamassi I, Sayed-Mouchaweh M, Hammami M, et al. Discussion and review on evolving data streams and concept drift adapting[J]. Evolving Systems, 2018, 9(1):1-23. [10] Singh M, Khilar P M. Mobile beacon based range free localization method for wireless sensor networks[J]. Wireless Networks, 2017, 23(4):1285-1300. |