MOAN
发表于 2025-3-26 23:31:07
Talent Identification in Football Using Supervised Machine Learningother valuable insights gleaned from the results pave the way for further research endeavors. The study aims to encourage the adoption of advanced data analytics and statistical methods within football clubs worldwide.
GRACE
发表于 2025-3-27 02:45:51
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婴儿
发表于 2025-3-27 05:51:44
Conference proceedings 20252024, held in Tonantzintla, Mexico in October 21–25, 2024...The 37 full papers presented in these proceedings were carefully reviewed and selected from 141 submissions. The papers presented in these two volumes are organized in the following topical sections:..Part I - Machine Learning; Computer Vis
senile-dementia
发表于 2025-3-27 12:35:46
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转换
发表于 2025-3-27 16:33:08
Latent State Space Quantization for Learning and Exploring Goals maximum volume of seen states while simultaneously exploring to acquire new knowledge about the environment. Through experiments, we demonstrate the effectiveness of the proposed framework in multi-goal learning across diverse domains: continuous and discrete mazes. We found that our approach surpa
上下连贯
发表于 2025-3-27 20:50:30
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Estimable
发表于 2025-3-28 00:39:38
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细胞膜
发表于 2025-3-28 02:54:53
Machine Learning Implementation for Water Quality Monitoring in the Desert State of Sonoraand poorly maintained, making it an imperfect source of information. Nonetheless, important insights are extracted, such as the evolution of contamination over time, which reveals how contamination-free water has become more scarce, even reaching a point where there are no samples of high-quality wa
军械库
发表于 2025-3-28 08:04:17
Predicting Water Levels Using Gradient Boosting Regressor and LSTM Models: A Case Study of Lago de Crning models into water resource management to improve prediction accuracy and ensure sustainable water supply and disaster readiness. The study aims to develop and validate predictive models, evaluate their accuracy and reliability, and provide insights for integrating these models into water manag
拍下盗公款
发表于 2025-3-28 12:05:43
Efficiently Mining High Average Utility Co-location Patterns Using Maximal Cliques and Pruning Strats. First, neighboring instances are enumerated by using maximal cliques, and then they are further arranged into a specified two-level hash table structure. The keys in the first level are the initial possible candidates and the values are another hash table structure with keys that are spatial feat