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| Theories, Methodologies and Applications of Probabilistic Forecasting for Power Systems with Renewable Energy Sources 新能源电力系统概率预测理论与方法及其应用 Journal article
Dianli Xitong Zidonghua/Automation of Electric Power Systems, 2021,Volume: 45,Issue: 1,Page: 2-16
Authors: Wan，Can; Song，Yonghua
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Artificial intelligence Power system Prediction interval Probabilistic forecasting Renewable energy Uncertainty |
| A new SEAIRD pandemic prediction model with clinical and epidemiological data analysis on COVID-19 outbreak Journal article
Applied Intelligence, 2021
Authors: Liu，Xian Xian; Fong，Simon James; Dey，Nilanjan; Crespo，Rubén González; Herrera-Viedma，Enrique
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Asymptomatic cases COVID-19 Disease transmission Enhanced surveillance Interventions Novel coronavirus Risk assessment SEAIRD SEIR Severity |
| Dynamic swarm class rebalancing for the process mining of rare events Journal article
Journal of Supercomputing, 2021
Authors: Li，Jinyan; Wu，Yaoyang; Fong，Simon; Wong，Raymond K.; Chu，Victor W.; Ong，Kok leong; Wong，Kelvin K.L.
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Class imbalance Classification Meta-heuristic Over-sampling Process mining Under-sampling |
| Fast Algorithm Based on Parallel Computing for Sample Entropy Calculation Journal article
IEEE Access, 2021
Authors: Dong X.; Chen C.; Geng Q.; Zhang W.; Zhang X.D.
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Acceleration Algorithm Biomedical Monitoring Entropy Fast Computation Graphics Processing Unit Graphics Processing Units Kernel Parallel Computing Sample Entropy Standards Time Series Analysis |
| A systematic literature review on intelligent automation: Aligning concepts from theory, practice, and future perspectives Journal article
Advanced Engineering Informatics, 2021,Volume: 47
Authors: Ng，Kam K.H.; Chen，Chun Hsien; Lee，C. K.M.; Jiao，Jianxin (Roger); Yang，Zhi Xin
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Adaptive decision making Artificial intelligence Innovative robotic process automation Intelligent automation |
| Prediction for Decision Support During the COVID-19 Pandemic Book chapter
出自: SpringerBriefs in Applied Sciences and Technology, 2021, 页码:
1-13
Authors: Marques，Joao Alexandre Lobo; Gois，Francisco Nauber Bernardo; Xavier-Neto，José; Fong，Simon James
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| Artificial Intelligence Prediction for the COVID-19 Data Based on LSTM Neural Networks and H2O AutoML Book chapter
出自: SpringerBriefs in Applied Sciences and Technology, 2021, 页码:
69-87
Authors: Marques，Joao Alexandre Lobo; Gois，Francisco Nauber Bernardo; Xavier-Neto，José; Fong，Simon James
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| Conclusion Book chapter
出自: SpringerBriefs in Applied Sciences and Technology, 2021, 页码:
73-74
Authors: Fong，Simon James; Dey，Nilanjan; Chaki，Jyotismita
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| ST-MGAT: Spatial-Temporal Multi-Head Graph Attention Networks for Traffic Forecasting Conference paper
Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI
Authors: Tian，Kelang; Guo，Jingjie; Ye，Kejiang; Xu，Cheng Zhong
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Graph Convolutional Networks Spatial-Temporal Model Traffic Forecasting |
| Automatic distinction between COVID-19 and common pneumonia using multi-scale convolutional neural network on chest CT scans Journal article
Chaos, Solitons and Fractals, 2020,Volume: 140
Authors: Yan，Tao; Wong，Pak Kin; Ren，Hao; Wang，Huaqiao; Wang，Jiangtao; Li，Yang
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Artificial intelligence Computed tomography COVID-19 pneumonia Mutile-scale convolutional neural network |
