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Titlebook: Applied Computational Intelligence in Engineering and Information Technology; Revised and Selected Radu-Emil Precup,Szilveszter Kovács,Emil

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41#
發(fā)表于 2025-3-28 17:18:19 | 只看該作者
VLearning, a New Direction for eLearning Challenges,ivation slightly subconsciously. This chapter outlines the development of this technology starting from eLearning to vLearning, as well as analyzes the most significant components of the mentioned technology, with the use of which education strives to make pace with the challenges of the present era.
42#
發(fā)表于 2025-3-28 22:46:08 | 只看該作者
43#
發(fā)表于 2025-3-28 23:48:51 | 只看該作者
A Case Study on Hardware/Software Codesign in Embedded Artificial Neural Networks,nue to find usage in embedded systems, it has become imperative to efficiently optimize their implementation within a short development cycle. Modest speedups can be easily achieved with these automated hardware/software codesign tools on the benchmarks examined.
44#
發(fā)表于 2025-3-29 05:43:00 | 只看該作者
45#
發(fā)表于 2025-3-29 09:25:32 | 只看該作者
46#
發(fā)表于 2025-3-29 12:48:22 | 只看該作者
https://doi.org/10.1007/b138882tion system. We describe our work in progress regarding highly realistic models of human behaviour and the impact of ontological reasoning on real-time simulations. We illustrate our approach in the context of the EDA project A-0938-RT-GC EUSAS, where we plan to implement it.
47#
發(fā)表于 2025-3-29 17:15:47 | 只看該作者
Background on Continuum Damage Mechanics,usly by the authors. Digital implementation aspects are given. The applications deal with speed and position control of rapid plants in mechatronic systems with focus on electrical drives with BLDC motors and variable moment of inertia.
48#
發(fā)表于 2025-3-29 20:15:07 | 只看該作者
Background on Continuum Damage Mechanics,ments of the Nash equilibrium. An evolutionary technique based on non-domination is proposed in order to detect the strong Berge and strong Berge Pareto equilibria. Some numerical experiments are presented in order to illustrate the proposed method.
49#
發(fā)表于 2025-3-30 01:08:42 | 只看該作者
https://doi.org/10.1007/b138882 start from an initial rule base that is created using fuzzy c-means clustering of a sample data set. The first examined optimization approach is the cross-entropy method while the second one is a hill-climbing based technique. We compare them in case of four benchmarking problems.
50#
發(fā)表于 2025-3-30 06:25:14 | 只看該作者
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