By Xue-Quan Xu, Xian-Bin Wen, Yue-Qing Li, Jin-Juan Quan (auth.), De-Shuang Huang, Laurent Heutte, Marco Loog (eds.)
The foreign convention on clever Computing (ICIC) was once shaped to supply an annual discussion board devoted to the rising and difficult issues in synthetic intelligence, computing device studying, bioinformatics, and computational biology, and so forth. It goals to deliver - gether researchers and practitioners from either academia and to percentage rules, difficulties and suggestions concerning the multifaceted points of clever computing. ICIC 2007, held in Qingdao, China, August 21-24, 2007, constituted the 3rd - ternational convention on clever Computing. It equipped upon the good fortune of ICIC 2006 and ICIC 2005 held in Kunming and Hefei, China, 2006 and 2005, respectively. This yr, the convention targeted typically at the theories and methodologies in addition to the rising purposes of clever computing. Its goal used to be to unify the image of latest clever computing concepts as an crucial idea that highlights the tendencies in complex computational intelligence and bridges theoretical examine with purposes. for that reason, the subject matter for this convention used to be “Advanced clever Computing expertise and Applications”. Papers concentrating on this subject have been solicited, addressing theories, methodologies, and functions in technological know-how and technology.
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Additional info for Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence: Third International Conference on Intelligent Computing, ICIC 2007, Qingdao, China, August 21-24, 2007. Proceedings
Oxford University Press. (1999) 12. : Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. The MIT Press, Cambridge, Massachusetts. (2001) 13. : Spiking Neuron Models: Single Neurons, pulations, Plasticity. Cambridge University Press. (2002) 14. : Simulation of High-Conductance States in Cortical Neural Networks, Masters thesis, University of Heidelberg, HD-KIP-03-22. (2003) 15. : Learning Mechanism in Networks of spiking Neurons. Studies in Computational Intelligence, Springer-Verlag.
6. One-step forward prediction JVM heap memory usage (a) Prediction data, (b) Error between original data and prediction data Table 1. H. Ning et al. 5 Conclusions The effectiveness of wavelet network with adaptive PSO algorithm for aging prediction has been investigated. The original time series is preprocessed by primary component analysis. Then the primary components are predicted by means of wavelet network and an algorithm of back-propagation based on adaptive iterative gradient descent method with adaptive PSO algorithm is proposed for wavelet network learning.
0267 The actual values and estimate values of xi in the algorithms (2) and (4) with the initial string (−2, −1)T . Times 12 Z. 0001 The actual values and estimate values of xi in the algorithms (2) and (4) with the initial string (1, 2)T . 0001 The actual values and estimate values of xi in the algorithms (2) and (4) with the initial string (−2, 1)T . Times 6 Conclusion In this paper, we analyze global convergence and learning parameters of the back-propagation algorithm for quadratic functions, present some theoretical results on global convergence conditions of the steepest descent algorithm with momentum (and without momentum) by directly analyzing the exact momentum equations for quadratic cost functions.