1 citations · 1 across the 5 of their papers we have counts for
6 papers
AETHER-P3 Nowcast v1.0: Model Description, Training-Data Construction, and Validation Technical report prepared in support of CCMC onboarding
Ruochen Wang, Xiaoli Bai
AETHER-P\textsuperscript{3} Nowcast v1.0 is a machine-learning-based global thermospheric neutral-density model developed for low-Earth-orbit applications and prepared for onboardi…
A Machine-Learning-Based Global Thermospheric Density Forecasting Model
Ruochen Wang, Xiaoli Bai
Thermospheric mass density governs aerodynamic drag in low Earth orbit and is a primary source of uncertainty in orbit prediction and conjunction assessment, particularly during ge…
Addressing Challenges in Time Series Forecasting: A Comprehensive Comparison of Machine Learning Techniques
Seyedeh Azadeh Fallah Mortezanejad, Ruochen Wang
The explosion of Time Series (TS) data, driven by advancements in technology, necessitates sophisticated analytical methods. Modern management systems increasingly rely on analyzin…
Physics-Informed Neural Networks with Unknown Partial Differential Equations: an Application in Multivariate Time Series
Seyedeh Azadeh Fallah Mortezanejad, Ruochen Wang, Ali Mohammad-Djafari
A significant advancement in Neural Network (NN) research is the integration of domain-specific knowledge through custom loss functions. This approach addresses a crucial challenge…
Signed Rank Chart For Tied Observations: An Application of Deep Learning Models
Seyedeh Azadeh Fallah Mortezanejad, Ruochen Wang
Shewhart Control Charts (SCC)s are constructed under the assumption of normality and are widely recognized in statistical quality control by numerous researchers. Problems arise wh…
Dependence control chart using maximum copula entropy
Seyedeh Azadeh Fallah Mortezanejad, Ruochen Wang, Gholamreza Mohtashami Borzadaran +1
Statistical quality control methods are noteworthy to producing standard production in manufacturing processes. In this regard, there are many classical manners to control the proc…