A comprehensive review of digital twin—part 1: modeling and twinning enabling technologies
As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented
attention because of its promise to further optimize process design, quality control, health …
attention because of its promise to further optimize process design, quality control, health …
Time-series forecasting with deep learning: a survey
Numerous deep learning architectures have been developed to accommodate the diversity
of time-series datasets across different domains. In this article, we survey common encoder …
of time-series datasets across different domains. In this article, we survey common encoder …
Challenges in predictive maintenance–A review
Predictive maintenance (PdM) aims the reduction of costs to increase the competitive
strength of the enterprises. It uses sensor data together with analytics techniques to optimize …
strength of the enterprises. It uses sensor data together with analytics techniques to optimize …
Digital twin: Values, challenges and enablers from a modeling perspective
Digital twin can be defined as a virtual representation of a physical asset enabled through
data and simulators for real-time prediction, optimization, monitoring, controlling, and …
data and simulators for real-time prediction, optimization, monitoring, controlling, and …
State-of-charge estimation of lithium-ion batteries using LSTM and UKF
For lithium iron phosphate battery, the ambient temperature and the flat open circuit voltage-
state-of-charge (SOC) curve are two of the major issues that influence the accuracy of SOC …
state-of-charge (SOC) curve are two of the major issues that influence the accuracy of SOC …
Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review
Accurate health estimation and lifetime prediction of lithium-ion batteries are crucial for
durable electric vehicles. Early detection of inadequate performance facilitates timely …
durable electric vehicles. Early detection of inadequate performance facilitates timely …
Scalable gradients for stochastic differential equations
The adjoint sensitivity method scalably computes gradients of solutions to ordinary
differential equations. We generalize this method to stochastic differential equations …
differential equations. We generalize this method to stochastic differential equations …
[图书][B] Mathematics for machine learning
The fundamental mathematical tools needed to understand machine learning include linear
algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability …
algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability …
Using inertial sensors for position and orientation estimation
In recent years, MEMS inertial sensors (3D accelerometers and 3D gyroscopes) have
become widely available due to their small size and low cost. Inertial sensor measurements …
become widely available due to their small size and low cost. Inertial sensor measurements …
[图书][B] State estimation for robotics
TD Barfoot - 2024 - books.google.com
A key aspect of robotics today is estimating the state (eg, position and orientation) of a robot,
based on noisy sensor data. This book targets students and practitioners of robotics by …
based on noisy sensor data. This book targets students and practitioners of robotics by …