微不足道
发表于 2025-3-30 08:28:41
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Odyssey
发表于 2025-3-30 13:06:51
Robust Control of Perishable Inventory with Uncertain Lead Time Using Neural Networks and Genetic Albest of the worst” case) controller parameters. We incorporate lead-time specific perturbations through plausible scenarios using several lead times sets. Based on extensive numerical experiments, the obtained solutions highlight that the approach provides stable and robust solutions even for high lead times.
Generosity
发表于 2025-3-30 19:50:24
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轻快走过
发表于 2025-3-30 23:56:53
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乞讨
发表于 2025-3-31 01:14:30
Classifying Anomalous Members in a Collection of Multivariate Time Series Data Using Large Deviationultivariate time series. We demonstrate the applicability of the proposed . (LAD) algorithm in identifying counties in the United States with anomalous trends in terms of COVID-19 related cases and deaths. Several of the identified anomalous counties correlate with counties with documented poor response to the COVID pandemic.
Urologist
发表于 2025-3-31 07:24:33
Adaptive Regularization of B-Spline Models for Scientific Data oscillations. Our method varies the strength of a smoothing parameter throughout the domain automatically, removing artifacts in poorly-constrained regions while leaving other regions unchanged. The behavior of our method is validated on a collection of two- and three-dimensional data sets produced by scientific simulations.
虚假
发表于 2025-3-31 12:33:34
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能量守恒
发表于 2025-3-31 16:58:16
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Repatriate
发表于 2025-3-31 19:07:23
https://doi.org/10.1007/978-3-030-73585-2 the input matrices. We also show that following the LAPACK QR design convention, while still useful, is significantly outperformed by unconventional code structures that increase data reuse. The performance results show multi-fold speedups against the state of the art libraries on the latest GPU architectures from both NVIDIA and AMD.
斜
发表于 2025-3-31 23:45:28
https://doi.org/10.1007/978-3-319-09707-7nce and its . nearest minority neighbors. Furthermore, Euclidean distance-based sample optimization is developed for improved imbalance classification. Finally, late fusion based on majority voting is utilized to obtain final predictions. Experiment results on 15 KEEL datasets demonstrate the great effectiveness of our proposed method.