Spinal-Fusion 发表于 2025-3-25 04:37:51
http://reply.papertrans.cn/24/2326/232532/232532_21.png琐事 发表于 2025-3-25 10:35:48
PDDL Planning and Ontologies, a Tool for Automatic Composition of Intentional-Contextual Web Servicomposition Architecture (CISCA) for implementing this approach. In the same way, we will present an AI planning technique to solve a composition problem, namely, the Planning Domain Description Language (PDDL) and the basis for reciprocal transformation with the Web Ontology Language (OWL).供过于求 发表于 2025-3-25 12:16:08
QSAR Anti-HIV Feature Selection and Prediction for Drug Discovery Using Genetic Algorithm and Machin parameters sensibility is equal to 0.99, specificity is equal to 0.91, and accuracy is equal to 0.98. These results reveal the capacity for achieving data subset of molecular descriptors, with high predictive capacity as well as the effectiveness and robustness of the proposed approach.训诫 发表于 2025-3-25 16:30:19
http://reply.papertrans.cn/24/2326/232532/232532_24.png全能 发表于 2025-3-25 20:44:45
http://reply.papertrans.cn/24/2326/232532/232532_25.png航海太平洋 发表于 2025-3-26 03:35:56
Das Grundkonzept der Marktzinsmethode project, we aim to examine the performance of two advanced neural network models, namely, convolutional neural networks and recurrent neural networks, and choose the most suitable one in terms of resistance and effectiveness for this particular application. This paper presents the simulations carried out and the results obtained.Arrhythmia 发表于 2025-3-26 05:22:51
Traffic Sign Detection: A Comparative Study Between CNN and RNN, project, we aim to examine the performance of two advanced neural network models, namely, convolutional neural networks and recurrent neural networks, and choose the most suitable one in terms of resistance and effectiveness for this particular application. This paper presents the simulations carried out and the results obtained.stress-test 发表于 2025-3-26 09:49:18
http://reply.papertrans.cn/24/2326/232532/232532_28.png现任者 发表于 2025-3-26 14:06:56
https://doi.org/10.1007/978-3-658-45422-7stigate the use of Deep Q-Learning to optimize vehicle time loss. Finally, we discuss deeply the performance of our proposed DRL-based solution compared to similar traditional programming-based systems.Intruder 发表于 2025-3-26 17:22:20
http://reply.papertrans.cn/24/2326/232532/232532_30.png