Page 263 - 《软件学报》2021年第10期
P. 263

李豁然  等:基于细粒度数据的智能手机续航时间预测模型                                                     3235


                [16]    Zhao X, Guo Y, Feng Q, et al. A system context-aware approach for battery lifetime prediction in smart phones. In: Proc. of the
                     2011 ACM Symp. on Applied Computing. ACM, 2011. 641646.
                [17]    Kang  JM, Seo S,  Hong  JWK. Personalized battery lifetime  prediction for  mobile devices based on usage patterns. Journal of
                     Computing Science and Engineering, 2011,5(4):338345.
                [18]    Kim D, Chon Y, Jung W, et al. Accurate prediction of available battery time for mobile applications. ACM Trans. on Embedded
                     Computing Systems (TECS), 2016,15(3):48.
                [19]    Aharony N, Pan W, Ip C, et al. Social fMRI: Investigating and shaping social mechanisms in the real world. Pervasive and Mobile
                     Computing, 2011,7(6):643659.
                [20]    Breiman L. Random forests. Machine Learning, 2001,45(1):532.
                [21]    Friedman JH. Stochastic gradient boosting. Computational Statistics & Data Analysis, 2002,38(4):367378.
                [22]    Friedman JH. Greedy function approximation: A gradient boosting machine. Annals of Statistics, 2001, 11891232.
                [23]    Chen T, Guestrin C. Xgboost: A scalable tree boosting system. In: Proc. of the 22nd ACM SIGKDD Int’l Conf. on Knowledge
                     Discovery and Data Mining. ACM, 2016. 785794.
                [24]    Pedregosa F, Varoquaux G, Gramfort A, et al. Scikit-learn: Machine learning in Python. Journal of Machine Learning Research,
                     2011,12(Oct.):28252830.
                [25]    Armstrong JS. Evaluating forecasting methods. In: Principles of Forecasting. Boston: Springer-Verlag, 2001. 443472.
                [26]    Hyndman RJ, Koehler AB. Another look at measures of forecast accuracy. Int’l Journal of Forecasting, 2006,22(4):679688.
                [27]    Smucker MD, Allan J, Carterette B. A comparison of statistical significance tests for information retrieval evaluation. In: Proc. of
                     the 16th ACM Conf. on Information and Knowledge Management. ACM, 2007. 623632.


                              李豁然(1992-),男,博士生,主要研究领域                      梅俏竹(1982-),男,博士,教授,博士生导
                              为软件工程,移动互联网,应用机器学习.                          师,主要研究领域为信息检索,机器学习,
                                                                           网络挖掘.



                              刘譞哲(1980-),男,博士,研究员,博士生                      梅宏(1963-),男,博士,中国科学院院士,
                              导师,CCF 高级会员,主要研究领域为服务                        博士生导师,CCF 会士,主要研究领域为软
                              计算,系统软件.                                     件工程,系统软件.
   258   259   260   261   262   263   264   265   266   267   268