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Titlebook: Computational Science - ICCS 2006; 6th International Co Vassil N. Alexandrov,Geert Dick Albada,Jack Dongar Conference proceedings 2006 Spri

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11#
發(fā)表于 2025-3-23 13:09:48 | 只看該作者
12#
發(fā)表于 2025-3-23 14:22:11 | 只看該作者
Jelena ?ivanovi? Miljkovi?,Tijana Crn?evi?ty requirements analysis. Details are presented of the evaluation process and the relative results of the six HPC systems evaluated. These include the more than 2-times speedup obtained by Cray by tuning the source code of the most important application.
13#
發(fā)表于 2025-3-23 19:08:37 | 只看該作者
14#
發(fā)表于 2025-3-24 01:22:34 | 只看該作者
15#
發(fā)表于 2025-3-24 05:28:46 | 只看該作者
The AWE HPC Benchmarkty requirements analysis. Details are presented of the evaluation process and the relative results of the six HPC systems evaluated. These include the more than 2-times speedup obtained by Cray by tuning the source code of the most important application.
16#
發(fā)表于 2025-3-24 06:59:25 | 只看該作者
A Transformation Tool for ODE Based Modelsrability with other tools used for mathematical modeling, mainly considering that it is based on Web architecture. The resulting work is a Web portal that transforms an ODE model documented in MathML to a C++ API that offers numerical solutions for that model.
17#
發(fā)表于 2025-3-24 13:38:17 | 只看該作者
Image-Based Robust Control of Robot Manipulators with Integral Actionshe steady-state. The stability of the closed-loop system is shown by Lyapunov method. The effectiveness of the proposed method is shown by simulation and ex periment results on the 5-link robot manipulators with two degree of freedom.
18#
發(fā)表于 2025-3-24 16:44:21 | 只看該作者
19#
發(fā)表于 2025-3-24 21:41:12 | 只看該作者
Sustainable Agriculture in Egyptlecular dynamics simulations as an alternative to particle-mesh and Ewald Summation methods which suffer from large errors due to various differentiation schemes. Our algorithm has .(...log .) complexity where . is typically a small constant.
20#
發(fā)表于 2025-3-25 02:28:44 | 只看該作者
Alternate Learning Algorithm on Multilayer Perceptrons, input-to-hidden, alternately trained. This algorithm requires less computational time for learning than the backpropagation with momentum and is shown in a parity check problem to be relatively reliable on the overall performance.
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