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Titlebook: Computational Science and Its Applications -- ICCSA 2012; 12th International C Beniamino Murgante,Osvaldo Gervasi,Bernady O. Apdu Conferenc

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Global Hybrid Ant Bee Colony Algorithm for Training Artificial Neural Networksordinary ABC, Levenberg-Marquardt (LM) training algorithms. From the investigated results, the proposed GHABC algorithm did get better the learning efficiency for NNs using Boolean Function classification task.
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Swarm Grid: A Proposal for High Performance of Parallel Particle Swarm Optimization Using GPGPUan reduce total execution time drastically and also, improve greatly the optimization process convergence. These parameters include the number of swarms and that of particles per swarm, together with their mapping into blocks and threads, respectively. All the swarms and particles therein operate in
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An Artificial Immune System Approach to Associative Classificationach generates dramatically less rules than traditional AC algorithms. Hence, the proposed approach is indeed significantly more efficient than traditional AC algorithms while achieving good competitive accuracy.
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Axis-Parallel Dimension Reduction for Biometric Research FAR (False Accept Rate) and FRR (False Reject Rate) both individually and if used together. Finally, the last section proposes the alternative multimodal system architecture with additional features that can further improve system performance in terms of accuracy and circumvention.
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Processor Allocation for Optimistic Parallelization of Irregular Programsally, and the runtime system detects conflicts between concurrent activities, aborting and rolling back conflicting tasks. However, parallelism in irregular algorithms is very complex. In a regular algorithm like dense matrix multiplication, the amount of parallelism can usually be expressed as a fu
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