By Yongquan Zhou, Yanlian Du, Zhengxin Huang (auth.), De-Shuang Huang, Martin McGinnity, Laurent Heutte, Xiao-Ping Zhang (eds.)
The foreign convention on clever Computing (ICIC) used to be shaped to supply an annual discussion board devoted to the rising and tough themes in synthetic intel- gence, computing device studying, trend reputation, photograph processing, bioinformatics, and computational biology. It goals to assemble researchers and practitioners from either academia and to proportion rules, difficulties, and ideas concerning the m- tifaceted features of clever computing. ICIC 2010, held in Changsha, China, August 18-21, 2010, constituted the sixth - ternational convention on clever Computing. It outfitted upon the luck of ICIC 2009, ICIC 2008, ICIC 2007, ICIC 2006, and ICIC 2005, that have been held in Ulsan, Korea, Shanghai, Qingdao, Kunming and Hefei, China, respectively. This 12 months, the convention targeted almost always at the theories and methodologies in addition to the rising functions of clever computing. Its objective used to be to unify the image of up to date clever computing recommendations as an fundamental idea that highlights the tendencies in complex computational intelligence and bridges theoretical learn with purposes. consequently, the subject for this convention was once “Advanced clever Computing know-how and Applications.” Papers targeting this topic have been solicited, addressing theories, methodologies, and purposes in technological know-how and technology.
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Extra info for Advanced Intelligent Computing Theories and Applications: 6th International Conference on Intelligent Computing, ICIC 2010, Changsha, China, August 18-21, 2010. Proceedings
5] provide a case-base reasoning (CBR) method to achieve the self-configuration in large scale systems. Although by using CBR, self configuration can be achieved to some extent in the system but it requires the change in existing cases as there can be a change in the existing elements because of the new element. Weighted graphs  is another approach to achieve self configuration. Multiple actions-based solutions of the problem are computed using dynamic programming and greedy algorithms. But the problem in this approach is that there is no measure for monitoring the health of the system after the execution of the algorithm that system is working normal or not.
As an efficient integration of learning methods, it has been used in various fields such as pattern recognition and machine learning of high-dimensional classification. For example, Bernard applied Random Forests to handwritten digit recognition, and satisfactory results have been obtained. In this paper, we propose a combination of the AdaBoost and Random forests in face detection. We use Random Forests as a weak learner of AdaBoost for selecting the high weight coefficients during the boosting process to improve the overfitting problem.
Self-Adaptive Fitness Formulation for Constrained Optimization. on Evolution Computation 7, 445–455 (2003) 8. : A Generic Framework for Constrained Optimization Using Genetic Algorithms. IEEE Trans. com Abstract. Collision detection is very important for improving the truth and immersion in the virtual environment. The paper analyzes the problems that exist in the normal algorithm. And there is no algorithm which is suitable to every situation. And the more complex the situations are, the more inefficient the algorithm is.