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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