This paper presents a comprehensive survey of machine learning, deep learning, and digital
twin technology methods for predicting and managing the battery state of health in electric …

With the rapid development of the new energy industry, supercapacitors have become key
devices in the field of energy storage. To forecast the remaining useful life (RUL) of …

In order to enhance the runoff prediction accuracy, an ensemble prediction model based on
least squares support vector machine (LSSVM) is proposed by including variational mode …

Accurate short-term wind power prediction is crucial for the efficient and safe operation of
wind power systems. To enhance the accuracy of short-term wind power prediction, this …

The remaining useful life (RUL) of a lithium battery is an important index for an efficient
battery management system, and the accurate prediction of RUL is beneficial for designing a …

Accurate prediction of the state of health (SOH) of lithium-ion batteries is important for real-
time monitoring and safety control of lithium-ion batteries. In this paper, a hybrid kernel least …

Accurately predicting the State of Health (SOH) of lithium-ion batteries is essential for
ensuring their safe and reliable operation, and reducing maintenance and service costs for …

To improve the accuracy of short term traffic flow prediction and to solve the problems of
nonlinearity of short term traffic flow, more noise in the data, and more difficult to determine …

The Dung Beetle Optimization (DBO) algorithm is a powerful metaheuristic algorithm that is
widely used for optimization problems. However, the DBO algorithm has limitations in …

Abstract The State of Health (SOH) of lithium-ion batteries significantly impacts the
performance, safety, and reliability of the battery, making it a crucial component of the battery …