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IEEE-SSCI 2013: Technical Program
IEEE Symposium on Computational Intelligence in Dynamic and Uncertain
Environments (IEEE CIDUE 2013)
IEEE CIDUE 2013 is the second IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments,
following its inception in 2011 in Paris by the same orgainzers. The purpose of this symposium is to bring together scientists,
engineers, and graduate students to present and discuss recent advances in employing CI for solving scientific and
engineering problems in the presence of uncertainties.
After a peer review process, 14 papers have been accepted for oral presentation from 16 high-quality submissions. Theses
accepted papers represent most recent advances in algorithm development as well as applications of CI techniques in
optimization and learning in dynamic and uncertain environments. One Keynote speech by Prof Y. Jin will be delivered, providing
an overview of the state-of-the-art in evolutionary optimization in uncertain environments and focusing on emerging
new ideas and real-world applications. It is hoped that this symposium will further promote the synergies between research
efforts on evolution and learning in uncertain environments, and attract interests of more young researchers and industrial
practitioners to this continuously growing area.
Co-Chair(s)
Yaochu Jin
University of Surrey, UK
Program Committee
Robi Polikar
Rowan University, USA
Hamid Bouchachia, University of Klagenfurt, Austria
Anabela Simoes, University of Coimbra, Portugal
Peter Bosman, Centrum voor Wiskunde en Informatica,
The Netherlands
Ke Tang, University of Science and Technology of China, China
David Pelta, University of Granada, Spain
Ponnuthurai Suganthan, Nanyang Tech. University, Singapore
Manuel Roveri, University of Pisa, Italy
Albert Bifet, University of Waikato, New Zealand
Gregory Ditzler, Drexel University, USA
Cesare Alippi, Politecnico di Milano, Italy
Juergen Branke, University of Wawick, UK
Hui Cheng, University of Bedfordshire
Chi-Keong Goh, Rolls-Royce Advanced Technology Centre, Singapore
Haibo He, University of Rhode Island, USA
Ivan Koychev, Bulgarian Academy of Sciences, Bulgaria
Xiaodong Li, RMIT University, Australia
Yew-Soon Ong, Nanyang Tech. University, Singapore
Hendrik Richter, Leipzig University of Applied Sciences
Philipp Rohlfshagen, University of Essex, UK
Moamar Sayed Mouchaweh, URCA, France
Qingfu Zhang, University of Essex, UK
Indr˙ežliobait ˙e, Bournemouth University, UK
Shengxiang Yang
Brunel University, UK
Shengxiang Yang, Brunel University, UK
Robi Polikar, Rowan University, USA
Yaochu Jin, University of Surrey, UK
Kay Chen Tan, National University of Singapore, Singapore
A. Sima Etaner-Uyar, Istanbul Technical University, Turkey
Dirk V. Arnold, Dalhousie University, Canada
Yingjie Yang, De Montfort University, UK
Jinliang Ding, Northeastern University, China
Xiaochuan Luo, Northeastern University, China
Shengping Yu, Northeastern University, China
Bin Li, University of Science and Technology of China, China
Carlos Coello Coello, CINVESTAV-IPN, Mexico
Swagatam Das, Indian Statictical Institute, India
Changhe Li, China University of Geosciences, China
Sanyou Zeng, China University of Geosciences, China
Xiaoyan Sun, China University of Mining and Technology
Dunwei Gong, China University of Mining and Technology
Maoguo Gong, Xidian University, China
Chuan-Kang Ting, National Chung Cheng University, ROC
Shih-Hsin Chen, Nanhua University, ROC
Aimin Zhou, East China Normal University, China
Haibin Duan, Beihang University
Keynote: Evolutionary Optimization in Dynamic and Uncertain Environments
By Prof. Yaochu Jin Chair: Andries Engelbrecht
Date/Time: 8.30 – 9.30, Wed. 17 April 2013 Venue: Lyrebird Level 3
Session: Surrogate-Assisted and Dynamic Optimization
Chair: Y. Jin Co-Chair: Engelbrecht Andries
Date/Time: 10.40 – 12.20, Wed. 17 April 2013 Venue: Canary I Level 4
SS-0172 Similarity-Based Evolution Control for Fitness Estimation in Particle Swarm Optimization—Chaoli Sun,
Jianchao Zeng, Jengshyang Pan and Yaochu Jin
SS-0495 Recurrent Neural Network Ensembles for Convergence Prediction in Surrogate-Assisted Evolutionary
Optimization—Christopher Smith, John Doherty and Yaochu Jin
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IEEE-CIDUE 2013