Proceedings of ELM-2015 Volume 2 Theory, Algorithms and Applications
This book contains some selected papers from the International Conference on Extreme Learning Machine 2015, which was held in Hangzhou, China, December 15-17, 2015. This conference brought together researchers and engineers to share and exchange R&D e
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Jiuwen Cao Kezhi Mao Jonathan Wu Amaury Lendasse Editors
Proceedings of ELM-2015 Volume 2 Theory, Algorithms and Applications (II)
Proceedings in Adaptation, Learning and Optimization Volume 7
Series editors Yew Soon Ong, Nanyang Technological University, Singapore e-mail: [email protected] Meng-Hiot Lim, Nanyang Technological University, Singapore e-mail: [email protected] Board of editors Hussain Abbas, University of New South Wales, Australia Giovanni Acampora, Nottingham Trent University, Nottingham, UK Enrique Alba, University of Málaga, Málaga, Spain Jonathan Chan, King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok, Thailand Sung-Bae Cho, Yonsei University, Seoul, Korea Hisao Ishibuchi, Osaka Prefecture University, Osaka, Japan Wilfried Jakob, Institute for Applied Computer Science (IAI), Germany Jose A. Lozano, University of the Basque Country UPV/EHU, Spain Zhang Mengjie, Victoria University of Wellington, Wellington, New Zealand Jim Smith, University of the West of England, Bristol, UK Kay-Chen Tan, National University of Singapore, Singapore Ke Tang, School of Computer Science and Technology, China Chuang-Kang Ting, National Chung Cheng University, Taiwan Donald C. Wunsch, Missouri University of Science & Technology, USA Jin Yaochu, University of Surrey, UK
About this Series The role of adaptation, learning and optimization are becoming increasingly essential and intertwined. The capability of a system to adapt either through modification of its physiological structure or via some revalidation process of internal mechanisms that directly dictate the response or behavior is crucial in many real world applications. Optimization lies at the heart of most machine learning approaches while learning and optimization are two primary means to effect adaptation in various forms. They usually involve computational processes incorporated within the system that trigger parametric updating and knowledge or model enhancement, giving rise to progressive improvement. This book series serves as a channel to consolidate work related to topics linked to adaptation, learning and optimization in systems and structures. Topics covered under this series include: • complex adaptive systems including evolutionary computation, memetic computing, swarm intelligence, neural networks, fuzzy systems, tabu search, simulated annealing, etc. • machine learning, data mining & mathematical programming • hybridization of techniques that span across artificial intelligence and computational intelligence for synergistic alliance of strategies for problem-solving • aspects of adaptation in robotics • agent-based computing • autonomic/pervasive computing • dynamic optimization/learning in noisy and uncertain environment • systemic alliance of stochastic and conventional search techniques • all aspects of adaptations in man-machine systems. This book series bridges the dichotomy of modern and conventional mathematical and heuristic/meta-heuristics approaches to bring about effective adaptation, learning and optimization. It p
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