用储层计算预测频繁相移的强迫范德波尔方程

IF 6.1 Machine learning with applications Pub Date : 2025-06-01 Epub Date: 2025-04-18 DOI:10.1016/j.mlwa.2025.100654
Sho Kuno , Hiroshi Kori
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引用次数: 0

摘要

我们测试了储层计算(RC)在预测特定非自治动力系统动力学方面的性能。具体来说,我们考虑了一个范德堡尔振荡器受到周期性外力频繁相移。油藏计算机利用特定相移产生的模拟数据进行训练和优化,用于预测不同相移的周期性外力作用下的振荡动力学。结果表明,如果训练数据具有足够的复杂性,则可以定量预测不同相移下的振荡动力学。这项研究的动机是预测轮班工人的昼夜节律和优化他们的轮班时间表的挑战。我们的研究结果表明,RC可以用于这些应用。
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Forecasting the forced van der Pol equation with frequent phase shifts using Reservoir Computing
We tested the performance of reservoir computing (RC) in predicting the dynamics of a specific nonautonomous dynamical system. Specifically, we considered a van der Pol oscillator subjected to a periodic external force with frequent phase shifts. The reservoir computer, trained and optimized using simulation data generated for a specific phase shift, was designed to predict the oscillation dynamics under periodic external forces with different phase shifts. The results suggest that if the training data exhibit sufficient complexity, it is possible to quantitatively predict the oscillation dynamics subjected to different phase shifts. This study was motivated by the challenge of predicting the circadian rhythm of shift workers and optimizing their shift schedules individually. Our results suggest that RC could be utilized for such applications.
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来源期刊
Machine learning with applications
Machine learning with applications Management Science and Operations Research, Artificial Intelligence, Computer Science Applications
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0.00%
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审稿时长
98 days
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