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Titlebook: Bioinspired Systems for Translational Applications: From Robotics to Social Engineering; 10th International W José Manuel Ferrández Vicente

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31#
發(fā)表于 2025-3-27 00:22:22 | 只看該作者
32#
發(fā)表于 2025-3-27 01:22:26 | 只看該作者
33#
發(fā)表于 2025-3-27 06:10:02 | 只看該作者
0302-9743 ral and Artificial Computation, IWINAC 2024, which took place in Olhao, Portugal, during June 4–7, 2024...The 99 full papers presented in these proceedings were carefully reviewed and selected from 193 submissions. They were organized in topical sections as follows:..Part I: Machine learning in neur
34#
發(fā)表于 2025-3-27 10:22:40 | 只看該作者
35#
發(fā)表于 2025-3-27 16:49:40 | 只看該作者
36#
發(fā)表于 2025-3-27 19:27:05 | 只看該作者
A Decentralized Collision Avoidance Algorithm for?Individual and?Collaborative UAVsposed by the interconnecting cable. The article outlines the algorithm’s theoretical foundation, implementation details, and provides comprehensive simulation results to demonstrate its efficacy in an experiment. The findings contribute to advancing the field of UAV swarm coordination and collision avoidance.
37#
發(fā)表于 2025-3-27 23:31:48 | 只看該作者
Refinement of?Protein Structures with?a?Memetic Algorithm. Examples with?SARS-CoV-2 Proteins for this refinement, including our memetic algorithm, which combines differential evolution with a state-of-the-art refinement method from the Rosetta environment. The comparison and analysis are performed with selected proteins from the SARS-CoV-2 virus.
38#
發(fā)表于 2025-3-28 05:20:47 | 只看該作者
Interdisciplinary Applied Mathematicsa very simple CNN model achieves high performance in surface defect classification on the NEU dataset thanks to image preprocessing and data augmentation. The initial F1-score of 0.9646 without image preprocessing increases to 0.9727 when preprocessing is carried out. The simple CNN then achieves an F1-score of 0.9854 after data augmentation.
39#
發(fā)表于 2025-3-28 07:51:00 | 只看該作者
https://doi.org/10.1007/978-0-387-68733-9nsic motivation based on frustration to prevent learning stagnation. Furthermore, the paper addresses the autonomous learning of world models, enabling the robot to identify its morphology, all within the framework of a cognitive architecture. Experimental results showcase the effectiveness of this approach in both real and simulated environments.
40#
發(fā)表于 2025-3-28 14:16:37 | 只看該作者
https://doi.org/10.1007/978-1-4020-3270-7rect evaluation by the standard fitness decoder. This combination of genetic diversity and heuristic knowledge aims to achieve superior solutions. This evaluation approach is applied to a genetic algorithm for scientific workflow scheduling, minimizing total execution time in cloud computing.
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