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A Breif Review on Data-driven Battery Health Estimation Methods for Energy Storage Systems., и . ICNSC, стр. 1-6. IEEE, (2022)A momentum-incorporated latent factorization of tensors model for temporal-aware QoS missing data prediction., , , и . Neurocomputing, (2019)Momentum-incorporated Latent Factorization of Tensors for Extracting Temporal Patterns from QoS Data., , , и . SMC, стр. 1757-1762. IEEE, (2019)A Diverse Biases Non-negative Latent Factorization of Tensors Model for Dynamic Network Link Prediction., , , , , и . ICNSC, стр. 1-6. IEEE, (2020)Adjusting Learning Depth in Nonnegative Latent Factorization of Tensors for Accurately Modeling Temporal Patterns in Dynamic QoS Data., , , , , и . IEEE Trans Autom. Sci. Eng., 18 (4): 2142-2155 (2021)An overview of data-driven battery health estimation technology for battery management system., , , , и . Neurocomputing, (мая 2023)MNL: A Highly-Efficient Model for Large-scale Dynamic Weighted Directed Network Representation., , и . IEEE Trans. Big Data, 9 (3): 889-903 (июня 2023)Efficient Representation to Dynamic QoS Data via Generalized Nesterov's Accelerated Gradient-incorporated Biased Non-negative Latent Factorization of Tensors., и . SMC, стр. 576-581. IEEE, (2021)Study on the Model of., , , , и . JCAI, стр. 363-366. IEEE Computer Society, (2009)