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State of health estimation of lithium-ion batteries based on regression techniques.

, and . ICCAD, page 493-498. IEEE, (2017)

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Reliable state of health condition monitoring of Li-ion batteries based on incremental support vector regression with parameters optimization., , , , and . J. Syst. Control. Eng., 237 (4): 717-727 (April 2023)State of health estimation of lithium-ion batteries based on regression techniques., and . ICCAD, page 493-498. IEEE, (2017)Direct Wind Turbine Drivetrain Prognosis Approach Using Elman Neural Network., , , , and . CoDIT, page 859-864. IEEE, (2018)Bi-spectrum based-EMD applied to the non-stationary vibration signals for bearing faults diagnosis., , , and . SoCPaR, page 25-30. IEEE, (2014)Particle filter-based prognostic approach for high-speed shaft bearing wind turbine progressive degradations., , , and . IECON, page 8099-8104. IEEE, (2017)Identification of early-stage Alzheimer's disease using SFAM neural network., , , , , and . Neurocomputing, (2014)Fast unsupervised nuclear segmentation and classification scheme for automatic allred cancer scoring in immunohistochemical breast tissue images., , , , , and . Comput. Methods Programs Biomed., (2018)Wind turbine drivetrain prognosis approach based on Kalman smoother with confidence bounds., , , and . ICIT, page 1865-1870. IEEE, (2018)A New Adaptive Prognostic Strategy Based on Online Future Evaluation and Extended Kalman Filtering., , , and . CoDIT, page 2033-2038. IEEE, (2019)Linear feature selection and classification using PNN and SFAM neural networks for a nearly online diagnosis of bearing naturally progressing degradations., , , , and . Eng. Appl. Artif. Intell., (2015)