兰州大学机构库

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Learning path adaptation in online learning systems 会议论文
Proceedings of the 2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2016, Nanchang, China, May 4, 2016 - May 6, 2016
Authors:  Muhammad, Alva;  Zhou, Qingguo;  Beydoun, Ghassan;  Xu, Dongming;  Shen, Jun
Favorite  |    Submit date:2017/01/18
E-learning  Interactive computer systems  Learning systems  Online systems  Students  Adaptive online learning  Learning objects  Learning paths  On-line learning systems  Personalized e-learning  Recent researches  State of the art  
GCN-GAN: Integrating Graph Convolutional Network and Generative Adversarial Network for Traffic Flow Prediction 期刊论文
IEEE Access, 2022, 卷号: 10, 页码: 94051-94062
Authors:  Zheng, Hongling;  Li, Xiang;  Li, Yongfeng;  Yan, Ziqin;  Li, Tinghong
Adobe PDF(2607Kb)  |  Favorite  |    Submit date:2022/11/08
Convolution  Flow graphs  Forecasting  Intelligent systems  Intelligent vehicle highway systems  Neural networks  Time series analysis  Traffic control  Convolutional neural network  Graph convolution and generative adversative neural network  Graph machine  Graph machine learning  Intelligent transport  Intelligent transport system  Intelligent transportation systems  Machine-learning  Neural-networks  Predictive models  Time series prediction  Time-series analysis  Transport systems  Generative adversarial networks  Convolutional neural networks  Data models  Machine learning  GCN-GAN  graph machine learning  time series prediction  
Model Construction and System Design of Natural Grassland-Type Recognition Based on Deep Learning 期刊论文
Remote Sensing, 2023, 卷号: 15, 期号: 4
Authors:  Xiu, Yangjing;  Ge, Jing;  Hou, Mengjing;  Feng, QS(冯琦胜);  Liang, TG(梁天刚);  Guo, Rui;  Chen, Jigui;  Wang, Qing
Favorite  |    Submit date:2023/07/18
Deep learning  Image enhancement  Image recognition  Large dataset  Learning systems  Meteorology  Transfer learning  Web crawler  Field grassland image  Grassland resource  Grassland types  Grassland-type recognition  Learning rates  Model construction  Pytorch  Recognition accuracy  Recognition systems  Transfer learning  grassland-type recognition  field grassland images  PyTorch  transfer learning  recognition system  
Buckley–James boosting model based on extreme learning machine and random survival forests 期刊论文
BIOMETRICAL JOURNAL, 2023, 卷号: 65, 期号: 5
Authors:  Kong, Jianfen;  Zhang, SH(张淑红)
Favorite  |    Submit date:2023/07/18
Adaptive boosting  Knowledge acquisition  Learning systems  Machine learning  Regression analysis  Boosting algorithm  Buckley–james model  Covariates  Ensemble learning  Extreme learning machine  Learning machines  Model-based OPC  Random survival forest  Survival analysis  Survival forests  Buckley-James model  ensemble learning  extreme learning machine  random survival forests  survival analysis  
Model Construction and System Design of Natural Grassland-Type Recognition Based on Deep Learning 期刊论文
Remote Sensing, 2023, 卷号: 15, 期号: 4
Authors:  Xiu, Yangjing;  Ge, Jing;  Hou, Mengjing;  Feng, QS(冯琦胜);  Liang, TG(梁天刚);  Guo, Rui;  Chen, Jigui;  Wang, Qing
Favorite  |    Submit date:2023/04/12
Deep learning  Image enhancement  Image recognition  Large dataset  Learning systems  Meteorology  Transfer learning  Web crawler  Field grassland image  Grassland resource  Grassland types  Grassland-type recognition  Learning rates  Model construction  Pytorch  Recognition accuracy  Recognition systems  Transfer learning  
Model Construction and System Design of Natural Grassland-Type Recognition Based on Deep Learning 期刊论文
Remote Sensing, 2023, 卷号: 15, 期号: 4
Authors:  Xiu, Yangjing;  Ge, Jing;  Hou, Mengjing;  Feng, QS(冯琦胜);  Liang, TG(梁天刚);  Guo, Rui;  Chen, Jigui;  Wang, Qing
Favorite  |    Submit date:2023/05/25
Deep learning  Image enhancement  Image recognition  Large dataset  Learning systems  Meteorology  Transfer learning  Web crawler  Field grassland image  Grassland resource  Grassland types  Grassland-type recognition  Learning rates  Model construction  Pytorch  Recognition accuracy  Recognition systems  Transfer learning  
Remote sensing retrieval based on machine learning algorithmUncertainty analysis 期刊论文
遥感学报, 2023, 卷号: 27, 期号: 3, 页码: 724-737
Authors:  Wang, Jingping;  Wu, XD(吴小丹);  Ma, Dujuan;  Wen, Jianguang;  Xiao, Qing
Favorite  |    Submit date:2023/09/04
Complex networks  Deep learning  Economic and social effects  Forestry  Learning algorithms  Learning systems  Neural networks  Sampling  Soil moisture  Support vector machines  Uncertainty analysis  Deep learning  Literature analysis  Machine learning algorithms  Machine-learning  On-machines  Quantitative remote sensing  Remote-sensing  Retrieval  Training sample  Uncertainty  
A wind speed forecasting model based on multi-objective algorithm and interpretability learning 期刊论文
ENERGY, 2023, 卷号: 269
Authors:  Li, M(李敏);  Yang, Y(杨裔);  He, Zhaoshuang;  Guo, Xinbo;  Zhang, RS(张瑞生);  Huang, Bingqing
Favorite  |    Submit date:2023/05/25
Wind speed forecasting  Partial mutual information  Machine learning algorithm  Perturbation  Interpretable learning  Energy utilization  Learning algorithms  Learning systems  Machine learning  Noise abatement  Reliability analysis  Wavelet decomposition  Wind power  Wind speed  Wind turbines  Absolute error  Forecasting models  Interpretability  Machine learning algorithms  Multi objective  Partial mutual informations  Search Algorithms  
Application advances of deep learning methods for de novo drug design and molecular dynamics simulation 期刊论文
Wiley Interdisciplinary Reviews-Computational Molecular Science, 2021, 卷号: 12, 期号: 3
Authors:  Bai, QF(白启峰);  Liu, Shuo;  Tian, Yanan;  Xu, Tingyang;  Banegas-Luna, Antonio Jesus;  Perez-Sanchez, Horacio;  Huang, Junzhou;  Liu, HX(刘焕香);  Yao, XJ(姚小军)
Favorite  |    Submit date:2021/12/15
de novo drug design  deep learning  explainable artificial intelligence  interpretable machine learning  MD simulation  Computational chemistry  Learning systems  Ligands  Deep learning  Design  De novo drug design  Drug Design  Drug discovery  Explainable artificial intelligence  Interaction mechanisms  Interpretable machine learning  Learning methods  Molecular force field  Novel ligands  
PM 2.5 concentration prediction in Lanzhou, China, using hyperchaotic cuckoo search—extreme learning machine 期刊论文
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2022
Authors:  Yang, Wenjing;  Du, J(杜娟);  Jia, Bowen;  Yang, L(杨凌);  Dong, Renze;  Li, Xinyi
Favorite  |    Submit date:2022/11/08
Chaotic systems  Knowledge acquisition  Machine learning  Mean square error  Multiple linear regression  Optimization  Concentration prediction  Cuckoo searches  Environmental problems  Extreme learning machine  Hyper-chaotic systems  Hyperchaotic  Lanzhou  Learning machines  PM 2.5  PM 2.5 prediction  Hyper  chaotic systems