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Ru Wang, Qingyu Zheng, Wei Li, Guijun Han, Xuan Wang and Song Hu
The uncertainty in the initial condition seriously affects the forecasting skill of numerical models. Targeted observations play an important role in reducing uncertainty in numerical prediction. The conditional nonlinear optimal perturbation (CNOP) meth...
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Andrea D?Ambrosio and Roberto Furfaro
This paper demonstrates the utilization of Pontryagin Neural Networks (PoNNs) to acquire control strategies for achieving fuel-optimal trajectories. PoNNs, a subtype of Physics-Informed Neural Networks (PINNs), are tailored for solving optimal control pr...
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Sheng Liu, Jian Song, Lanyong Zhang and Yinchao Tan
The three-degree-of-freedom (3-DOF) stabilized control system for ship propulsion-assisted sails is used to control the 3-DOF motion of sails to obtain offshore wind energy. The attitude of the sail is adjusted to ensure optimal thrust along the target c...
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Nattakan Supajaidee, Nawinda Chutsagulprom and Sompop Moonchai
Ordinary kriging (OK) is a popular interpolation method for its ability to simultaneously minimize error variance and deliver statistically optimal and unbiased predictions. In this work, the adaptive moving window kriging with K-means clustering (AMWKK)...
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Zitong Wang, Enrang Zheng, Jianguo Liu and Tuo Guo
Traditional methods of orthogonal basis function decomposition have been extensively used to detect magnetic anomaly signals. However, the determination of the relative velocity between the detection platform and the magnetic target remains elusive in pr...
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