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Transactions on Cybernetics
Scope
The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or between machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.
IEEE Transactions on Cybernetics replaced the IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics on January 1, 2013.
Subscribe to this Journal via RSS.Editor-in-Chief
C. L. Philip Chen
Editor-In-Chief
School of Computer Science and Engineering,
South China University of Technology, Guangzhou, 510641, China, and Faculty of Science and Technology, University of Macau, Macau, China.
Articles
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30 June 2020IEEE Transactions on CyberneticsPresents a listing of the editorial board, board of governors, current staff, committee members,...
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30 June 2020Predicting COVID-19 in China Using Hybrid AI ModelThe coronavirus disease 2019 (COVID-19) breaking out in late December 2019 is gradually being...
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30 June 2020Command Filter-Based Adaptive NN Control for MIMO Nonlinear Systems With Full-State Constraints and Actuator HysteresisThis article studies the issue of adaptive neural network (NN) control for strict-feedback...
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30 June 2020Event-Triggered Consensus of Linear Multiagent Systems With Time-Varying Communication DelaysIn this paper, the event-triggered consensus problem of linear multiagent systems with...
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19 June 2020Predicting COVID-19 in China Using Hybrid AI ModelThe coronavirus disease 2019 (COVID-19) breaking out in late December 2019 is gradually being...
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31 May 2019Ant Colony Stream Clustering: A Fast Density Clustering Algorithm for Dynamic Data StreamsA data stream is a continuously arriving sequence of data and clustering data streams requires...
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31 May 2017A Micro-GA Embedded PSO Feature Selection Approach to Intelligent Facial Emotion RecognitionThis paper proposes a facial expression recognition system using evolutionary particle swarm...
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30 September 2016Genetic Learning Particle Swarm OptimizationSocial learning in particle swarm optimization (PSO) helps collective efficiency, whereas...
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19 June 2020Deep Reinforcement Learning for Multiagent Systems: A Review of Challenges, Solutions, and ApplicationsReinforcement learning (RL) algorithms have been around for decades and employed to solve various...
