[1] 王青, 谭良. 基于用户主题精确感知大数据群体计算任务分配算法[J]. 计算机应用, 2016, 36(10):2777-2783. (WANG Q, TAN L. Optimization algorithm for accurately theme-aware task assignment in crowd computing on big data[J]. Journal of Computer Applications, 2016, 36(10):2777-2783.) [2] AGARWALLA S, SARMA K K. Machine learning based sample extraction for automatic speech recognition using dialectal Assamese speech[J]. Neural Networks, 2016, 78(C):97-111. [3] LVANOVIC D, KUPUSINAC A, STOKIC E, et al. ANN prediction of metabolic syndrome:a complex puzzle that will be completed[J]. Journal of Medical Systems, 2016, 40(12):264. [4] MOON T W, JUNG D H, CHANG S H, et al. Estimation of greenhouse CO2 concentration via an artificial neural network that uses environmental factors[J]. Horticulture Environment & Biotechnology, 2018, 59(1):45-50. [5] 胡丽娟, 刁赢龙, 刘科研, 等. 基于大数据技术的配电网运行可靠性分析[J]. 电网技术, 2017, 41(1):265-271.(HU L J, DIAO Y L, LIU K Y, et al. Operational reliability analysis of distribution network based on big data technology[J]. Power System Technology, 2017, 41(1):265-271.) [6] 田春山, 刘希林, 汪佳. 基于CF和Logistic回归模型的广东省地质灾害易发性评价[J]. 水文地质工程地质, 2016, 43(6):154-161.(TIAN C S, LIU X L, WANG J. Geohazard susceptibility assessment based on CF model and logistic regression models in Guangdong[J]. Hydrogeology & Engineering Geology, 2016, 43(6):154-161.) [7] LYU H M, SHEN J S, ARULRAJAH A. Assessment of geohazards and preventative countermeasures using AHP incorporated with GIS in Lanzhou, China[J]. Sustainability, 2018, 10(2):304. [8] LIN J W, CHEN C W, PENG C Y. Potential hazard analysis and risk assessment of debris flow by fuzzy modeling[J]. Natural Hazards, 2012, 64(1):273-282 [9] PEND S H. Hazard ratings of debris flow evacuation sites in hillside communities of Ershui township, Changhua County, Taiwan[J]. Water, 2016, 8(2):54. [10] NIU C C, WANG Q, CHEN J P, et al. Hazard assessment of debris flows in the reservoir region of Wudongde hydropower station in China[J]. Sustainability, 2015, 7(11):15099-15118. [11] KANG S, LEE S R, VASU N N, et al. Development of an initiation criterion for debris flows based on local topographic properties and applicability assessment at a regional scale[J]. Engineering Geology, 2017, 230:64-76. [12] RIVERA W A, XANTHOPOULOS P. A priori synthetic over-sampling methods for increasing classification sensitivity in imbalanced data sets[J]. Expert Systems with Applications, 2016, 66(C):124-135. [13] 霍玉丹, 谷琼, 蔡之华, 等. 基于遗传算法改进的少数类样本合成过采样技术的非平衡数据集分类算法[J]. 计算机应用, 2015, 35(1):121-124.(HUO Y D, GU Q, CAI Z H, et al. Classification method for imbalance dataset based on genetic algorithm improved synthetic minority over-sampling technique[J]. Journal of Computer Applications, 2015, 35(1):121-124.) [14] 盛贤君, 姜涛, 王杰, 等. 基于BP神经网络的速度前馈PID控制器设计[J]. 计算机应用, 2015, 35(S2):134-137. (SHENG X J, JIANG T, WANG J, et al. Speed-feed-forward PID controller design based on BP neural network[J]. Journal of Computer Applications, 2015, 35(S2):134-137.) [15] 王双, 李小春, 王少泉, 等. 碎石土级配特征对渗透系数的影响研究[J]. 岩石力学与工程学报, 2015, 34(2):4394-4402. (WANG S, LI X C, WANG S Q, et al. Study of gravel-soil gradation characteristics influence on the permeability coefficient[J]. Chinese Journal of Rock Mechanics and Engineering, 2015, 34(2):4394-4402.) [16] 中华人民共和国国土资源部. DZ/T 0220-2006, 泥石流灾害防治工程勘察规范[S]. 北京:中国标准出版社,2006:4. (Ministry of land and resources of the People's Republic of China. DZ/T 0220-2006 Specification of geological investigation for debris flow stabilization[S]. Beijing:Standards Press of China, 2006:4.) [17] 陈英义, 程倩倩, 成艳君, 等. 基于GA-BP神经网络的池塘养殖水温短期预测系统[J]. 农业机械学报, 2017, 48(8):172-178. (CHEN Y Y, CHENG Q Q, CHEN Y J. et al. Short-term prediction system of water temperature in pond aquaculture based on GA-BP neural network[J]. Transactions of the Chinese Society for Agricultural Machinery, 2017, 48(8):172-178.) [18] 余滨杉, 王社良, 杨涛, 等. 基于遗传算法优化的SMABP神经网络本构模型[J]. 金属学报, 2017, 53(2):248-256. (YU B S, WANG S L, YANG T, et al. BP neural network constitutive model based on optimization with genetic algorithm for SMA[J]. Acta Metallurgica Sinica, 2017, 53(2):248-256.) [19] 冯国奇, 崔东亮, 张亚军, 等. 样本视角下面向复杂产品多目标优化设计的混合人工神经网络-遗传算法技术[J]. 计算机集成制造系统, 2016, 22(6):1403-1414. (FENG G Q, CUI D L, ZHANG Y J, et al. Hybird NN-GA framework for multi-objective optimization of complex products design from perspective of sample management[J], Computer Integrated Manufacturing Systems, 2016, 22(6):1403-1414.) [20] 王嘉卿, 朱焱, 陈同孝, 等. 欺诈网页检测中基于遗传算法的特征优选[J]. 计算机应用, 2018, 38(1):295-299. (WANG J Q, ZHU Y, CHEN T X, et al. Optimum feature selection based on genetic algorithm under Web spam detection[J]. Journal of Computer Applications, 2018, 38(1):295-299.) [21] 徐新卫, 丁敬安, 柳智才, 等. 基于梯度提升决策模型的空间占用检测研究[J]. 计算机应用研究, 2019, 36(3):1-8. (XU X W, DING J A, LIU Z C, et al. Occupancy detection based on extreme gradient boosting decision model[J]. Application Research of Computers, 2019, 39(3):1-8.) |