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Titlebook: Advanced Intelligent Computing; 7th International Co De-Shuang Huang,Yong Gan,Juan Carlos Figueroa Conference proceedings 2012 Springer-Ver

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Big Bang Nucleosynthesis and Neutrinosuzzy C-means (FCM) cluster analysis of the principles and algorithms process at first, then a novel method to initialize the cluster centers is proposed. The idea is that the cluster centers’ distribution should be as evenly as possible within the input field. A “Two-step method” is used in our evol
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Richard Arnowitt,Bhaskar Dutta,Bo Hucal classifier, however, remains a challenging problem. Rather than selecting one single local classifier, in this paper, we propose to choose several local classifiers and use adaptive fusion strategy to alleviate the choice problem of the proper local classifier. Based on the fast and scalable loc
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Unification in Higher Dimensionshe node’s residual energy and distance with other cluster heads. In addition, the clusters send data to the base station by means of combination of single hop and multi-hop manner for saving cluster heads’ energy. Simulation results show that compared with LEACH and P-LEACH, the improved algorithm c
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Privatization , the Chinese State, parameter of the regularizer efficiently is still unanswered, especially for multi-class situation. In this paper, we first prove that regularizing LDA is equivalent to augmenting the training set in a specific way and thereby propose an efficient model selection criterion based on the principle of
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,Gyrogroups: Modeled on Einstein’s Addition, objects. Using a Boolean valued information system, certain rows or objects can be defined as ultimate maximum support object, ultimate minimum support object and zero significance parameter. One can then reduce a table by eliminating the defined row or objects in what has been defined as hybrid re
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