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Titlebook: Computational Science – ICCS 2020; 20th International C Valeria V. Krzhizhanovskaya,Gábor Závodszky,Jo?o T Conference proceedings 2020 Spri

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31#
發(fā)表于 2025-3-26 21:48:54 | 只看該作者
32#
發(fā)表于 2025-3-27 01:08:03 | 只看該作者
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發(fā)表于 2025-3-27 06:03:00 | 只看該作者
34#
發(fā)表于 2025-3-27 09:55:06 | 只看該作者
35#
發(fā)表于 2025-3-27 16:37:22 | 只看該作者
https://doi.org/10.1007/b138239cture for timely collection, reporting, and analysis of epidemic data undermines necessary preparedness and thus posing serious health challenges to the general public. By developing a simulation framework that models population dynamics and the interactions of both humans and mosquitoes, we may ena
36#
發(fā)表于 2025-3-27 18:09:52 | 只看該作者
37#
發(fā)表于 2025-3-27 22:46:21 | 只看該作者
Subhra R Mondal,Jana Majerova,Subhankar Dased by using partial differential equation with nonlinear term. The bouton is modeled as a distorted geosphere and the mitochondrion inside it as a highly modified cuboid. The quality of the mesh elements is examined. The changes of the amount of neurotransmitter during exocytosis are simulated.
38#
發(fā)表于 2025-3-28 04:20:46 | 只看該作者
HO Minh-Nhat,Jana Majerova,Subhankar Dasvironments, numerous populations of beings, and to increase the detail of models causes the need for parallelization of computations. The signal-based simulation algorithm, presented in our previous research, prove the possibility of linear scalability of such computations up?to thousands of computi
39#
發(fā)表于 2025-3-28 09:41:36 | 只看該作者
Oliver Vettori,Christian Rammelry operations, and/or energy production. There exist different methods for solving inverse problems, including gradient based methods, statistics based methods, and Deep Learning (DL) methods. In this work, we focus on the latest. Specifically, we study the design of proper loss functions for dealin
40#
發(fā)表于 2025-3-28 13:11:21 | 只看該作者
Palgrave Studies in Global Higher Educatione parts of adaptive dynamically changing tree. The paper focuses on adaptation of the classic HGS algorithm for multi-criteria optimization problems, coupling the HGS with Particle Swarm Optimization demes. The main contribution of the paper is showing the efficacy and efficiency of the actor-based
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