Equifinality, sloppiness, and emergent structures of mechanistic soil biogeochemical models
Biogeochemical models increasingly consider the microbial control of carbon cycling in soil.
The major current challenge is to validate mechanistic descriptions of microbial processes …
The major current challenge is to validate mechanistic descriptions of microbial processes …
Parameter calibration of wind farm with error tracing technique and correlated parameter identification
With the increasing penetrations of wind power in power systems, periodical calibration of
the large-scale Wind Farm (WF) model is crucial to maintaining high-quality model …
the large-scale Wind Farm (WF) model is crucial to maintaining high-quality model …
Symbolic regression for data-driven dynamic model refinement in power systems
AT Sarić, AA Sarić, MK Transtrum… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
This paper describes a data-driven symbolic regression identification method tailored to
power systems and demonstrated on different synchronous generator (SG) models. In this …
power systems and demonstrated on different synchronous generator (SG) models. In this …
[HTML][HTML] Bayesian, frequentist, and information geometric approaches to parametric uncertainty quantification of classical empirical interatomic potentials
Y Kurniawan, CL Petrie, KJ Williams… - The Journal of …, 2022 - pubs.aip.org
In this paper, we consider the problem of quantifying parametric uncertainty in classical
empirical interatomic potentials (IPs) using both Bayesian (Markov Chain Monte Carlo) and …
empirical interatomic potentials (IPs) using both Bayesian (Markov Chain Monte Carlo) and …
Data-driven symbolic regression for identification of nonlinear dynamics in power systems
AM Stanković, AA Sarić, AT Sarić… - 2020 IEEE Power & …, 2020 - ieeexplore.ieee.org
The paper describes a data-driven system identification method tailored to power systems
and demonstrated on models of synchronous generators (SGs). In this work, we extend the …
and demonstrated on models of synchronous generators (SGs). In this work, we extend the …
Multistage parameter identification featured generic wind farm dynamic equivalent modeling
With the high penetration of large-scale wind farms (WFs), accurate grid-connected WF
models are crucial to be developed for studying the stability of power grids. Due to the large …
models are crucial to be developed for studying the stability of power grids. Due to the large …
Simplified Information Geometry Approach for Massive MIMO-OFDM Channel Estimation--Part I: Algorithm and Fixed Point Analysis
In this two-part paper, we investigate the channel estimation for massive multiple-input
multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. In Part I …
multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. In Part I …
Chebyshev approximation and the global geometry of model predictions
Complex nonlinear models are typically ill conditioned or sloppy; their predictions are
significantly affected by only a small subset of parameter combinations, and parameters are …
significantly affected by only a small subset of parameter combinations, and parameters are …
Data-driven classification, reduction, parameter identification and state extension in hybrid power systems
AT Sarić, MK Transtrum… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The paper describes a manifold learning-based algorithm for big data classification and
reduction, as well as parameter identification in real-time operation of a power system. Both …
reduction, as well as parameter identification in real-time operation of a power system. Both …
Time-Varying ADN Load Modeling Considering the Suppression of the Plateau Phenomenon and Continuous Low-Quality Data
P Wang, Z Zhang, C Chen, Q Huang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The time-varying parameter identification of load models has attracted broad attention when
large amounts of intermittent distributed generations (DGs) and stochastic loads are …
large amounts of intermittent distributed generations (DGs) and stochastic loads are …