Journal of Shandong University(Engineering Science) ›› 2019, Vol. 49 ›› Issue (3): 108-113.doi: 10.6040/j.issn.1672-3961.0.2017.449
• Mechanical Engineering • Previous Articles Next Articles
Diankun ZHENG1(),Tongle XU1,*(),Zhaojie YIN1,Qingmin MENG2
CLC Number:
1 | 冯治刚, 王桂生, 吴晓荣, 等. 基于时间序列法的高拱坝强度安全裕度分析评价模型及应用[J]. 水电能源科学, 2013, 31 (11): 61- 64. |
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2 | 邱坤南, 沈斐敏. 小波多尺度分析的浸润线预测方法[J]. 福州大学学报(自然科学版), 2016, 44 (5): 746- 752. |
QIU Kunnan , SHEN Feimin . Research on infiltration route prediction method based on wavelet multi-resolution-analysis[J]. Journal of Fuzhou University(Natural Science Edition), 2016, 44 (5): 746- 752. | |
3 | 郎学政, 许同乐, 黄湘俊, 等. 利用PCA和神经网络预测尾矿坝地下水位[J]. 水文地质工程地质, 2014, 41 (2): 13- 17. |
LANG Xuezheng , XU Tongle , HUANG Xiangjun , et al. Research on prediction of groundwater levels near a tailing dam based on PCA and artificial neural network[J]. Hydrogeology and Engineering Geology, 2014, 41 (2): 13- 17. | |
4 | 何勇, 李妍琰. 改进粒子群优化BP神经网络的洪水智能预测模型研究[J]. 西南师范大学学报(自然科学版), 2014, 39 (5): 75- 80. |
HE Yong , LI Yanyan . On application of improved PSO-BP neural network in intelligent flood forecasting model[J]. Journal of Southwest China Normal University(Natural Science Edition), 2014, 39 (5): 75- 80. | |
5 |
程加堂, 艾莉, 熊燕. 基于IQPSO-BP算法的煤矿瓦斯涌出量预测[J]. 矿业安全与环保, 2016, 43 (4): 38- 41.
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CHENG Jiatang , AI Li , XIONG Yan . Coal mine gas emission prediction based on IQPSO-BP algorithm[J]. Mining Safety & Environmental Protection, 2016, 43 (4): 38- 41.
doi: 10.3969/j.issn.1008-4495.2016.04.010 |
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6 | 高峰, 冯民权, 滕素芬. 基于PSO优化BP神经网络的水质预测研究[J]. 安全与环境学报, 2015, 15 (4): 338- 341. |
GAO Feng , FENG Minquan , TENG Sufen . On the way for forecasting the water quality by BP neural network based on the PSO[J]. Journal of Safety and Environment, 2015, 15 (4): 338- 341. | |
7 |
潘少伟, 梁鸿军, 李良, 等. 改进PSO-BP神经网络对储层参数的动态预测研究[J]. 计算机工程与应用, 2014, 50 (10): 52- 56.
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PAN Shaowei , LIANG Hongjun , LI Liang , et al. Dynamic prediction on reservoir parameter by improved PSO-BP neural network[J]. Computer Engineering and Applications, 2014, 50 (10): 52- 56.
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8 | 邹卫霞, 王多万, 杜光龙. 基于粒子群优化的频域多信道干扰对齐算法[J]. 北京邮电大学学报, 2016, 39 (3): 22- 26. |
ZOU Weixia , WANG Duowan , DU Guanglong . On particle swarm optimization for multi-frequency channel interference alignment[J]. Journal of Beijing University of Posts and Telecommunications, 2016, 39 (3): 22- 26. | |
9 | 花景新, 薄煜明, 陈志敏. 基于改进粒子群优化神经网络的房地产市场预测[J]. 山东大学学报(工学版), 2014, 44 (4): 24- 32. |
HUA Jingxin , BO Yuming , CHEN Zhimin . Forecasting of real estate market based on particle swarm optimized neural network[J]. Journal of Shandong University (Engineering Science), 2014, 44 (4): 24- 32. | |
10 | GAO Z , LI X Z . The hybrid adaptive particle swarm optimization based on the average speed[J]. Control and Decision-Making, 2012, 27 (1): 152- 160. |
11 |
ZHOU C , TAO J C . Adaptive combination forecasting model for China's logistics freight volume based on an improved PSO-BP neural network[J]. Kybernetes, 2015, 44 (4): 646- 666.
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