Huifang Li
Orcid: 0000-0002-3688-5387Affiliations:
- Beijing Institute of Technology, State Key Laboratory of Intelligent Control and Decision of Complex Systems, School of Automation, China
- University of Toronto, Ontario, Canada (2016)
- University of California, Berkeley, CA, USA (2012)
- National University of Ireland, Galway, Ireland (2007 - 2008)
- Tinghua University, Department of Automation, Beijing, China (2001 - 1003)
- Xi'an Jiaotong University, Department of egrees in systems engineering, China (PhD 2000)
According to our database1,
Huifang Li
authored at least 20 papers
between 2014 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Bibliography
2024
Co-evolutionary and Elite learning-based bi-objective Poor and Rich Optimization algorithm for scheduling multiple workflows in the cloud.
Future Gener. Comput. Syst., March, 2024
2023
IEEE Trans. Cogn. Dev. Syst., March, 2023
J. Adv. Comput. Intell. Intell. Informatics, January, 2023
2022
Chaotic-Nondominated-Sorting Owl Search Algorithm for Energy-Aware Multi-Workflow Scheduling in Hybrid Clouds.
IEEE Trans. Sustain. Comput., 2022
Multi-Swarm Co-Evolution Based Hybrid Intelligent Optimization for Bi-Objective Multi-Workflow Scheduling in the Cloud.
IEEE Trans. Parallel Distributed Syst., 2022
Scoring and Dynamic Hierarchy-Based NSGA-II for Multiobjective Workflow Scheduling in the Cloud.
IEEE Trans Autom. Sci. Eng., 2022
Intelligent Fault Diagnosis for Large-Scale Rotating Machines Using Binarized Deep Neural Networks and Random Forests.
IEEE Trans Autom. Sci. Eng., 2022
Improved swarm search algorithm for scheduling budget-constrained workflows in the cloud.
Soft Comput., 2022
Mutation and dynamic objective-based farmland fertility algorithm for workflow scheduling in the cloud.
J. Parallel Distributed Comput., 2022
Weighted double deep Q-network based reinforcement learning for bi-objective multi-workflow scheduling in the cloud.
Clust. Comput., 2022
2021
PSO+LOA: hybrid constrained optimization for scheduling scientific workflows in the cloud.
J. Supercomput., 2021
Class Imbalanced Fault Diagnosis via Combining K-Means Clustering Algorithm with Generative Adversarial Networks.
J. Adv. Comput. Intell. Intell. Informatics, 2021
2020
Generative Oversampling and Deep Forest based Minority-class Sensitive Fault Diagnosis Approach.
Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020
Temporal Fusion Pointer network-based Reinforcement Learning algorithm for Multi-Objective Workflow Scheduling in the cloud.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
2018
Fault Diagnosis of Tennessee-Eastman Process Using Orthogonal Incremental Extreme Learning Machine Based on Driving Amount.
IEEE Trans. Cybern., 2018
A deep Boltzmann machine and multi-grained scanning forest ensemble collaborative method and its application to industrial fault diagnosis.
Comput. Ind., 2018
2015
Proceedings of the 2015 IEEE International Conference on Systems, 2015
Proceedings of the 2015 IEEE International Conference on Systems, 2015
Proceedings of the 2015 IEEE International Conference on Smart City/SocialCom/SustainCom/DataCom/SC2 2015, 2015
2014
Workflow scheduling algorithm based on control structure reduction in cloud environment.
Proceedings of the 2014 IEEE International Conference on Systems, Man, and Cybernetics, 2014