Results 1 to 10 of about 24,570,387 (263)
A protocol for dynamic model calibration. [PDF]
Brief Bioinform, 2022 Ordinary differential equation models are nowadays widely used for the mechanistic description of biological processes and their temporal evolution. These models typically have many unknown and nonmeasurable parameters, which have to be determined by ...
Villaverde AF +4 more
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Deep learning model calibration for improving performance in class-imbalanced medical image classification tasks. [PDF]
PLoS One, 2022 In medical image classification tasks, it is common to find that the number of normal samples far exceeds the number of abnormal samples. In such class-imbalanced situations, reliable training of deep neural networks continues to be a major challenge ...
Rajaraman S, Ganesan P, Antani S.
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Land Surface Model Calibration Using Satellite Remote Sensing Data. [PDF]
Sensors (Basel), 2023 Satellite remote sensing provides a unique opportunity for calibrating land surface models due to their direct measurements of various hydrological variables as well as extensive spatial and temporal coverage.
Khaki M.
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Time to Update the Split‐Sample Approach in Hydrological Model Calibration
Water Resources Research, 2022 Model calibration and validation are critical in hydrological model robustness assessment. Unfortunately, the commonly used split‐sample test (SST) framework for data splitting requires modelers to make subjective decisions without clear guidelines. This
Hongren Shen, B. Tolson, J. Mai
semanticscholar +1 more source
A Literature Review on Train Motion Model Calibration
IEEE transactions on intelligent transportation systems (Print), 2023 The dynamics of a moving train are usually described by means of a motion model based on Newton’s second law. This model uses as input track geometry data and train characteristics like mass, the parameters that model the running resistance, the maximum ...
Alex Cunillera +4 more
semanticscholar +1 more source
Sensors, 2021 Good air quality is essential for both human beings and the environment in general. The three most harmful air pollutants are nitrogen dioxide (NO2), ozone (O3) and particulate matter.
Diego Sales-Lérida +3 more
doaj +1 more source
A Generalized Weighted Monte Carlo Calibration Method for Derivative Pricing
Mathematics, 2021 The weighted Monte Carlo method is an elegant technique to calibrate asset pricing models to market prices. Unfortunately, the accuracy can drop quite quickly for out-of-sample options as one moves away from the strike range and maturity range of the ...
Hilmar Gudmundsson, David Vyncke
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Frontiers in Built Environment, 2022 The objective of this study is to examine a machine learning (ML) framework for calibrating the parameters of analytical models of complex nonlinear structural systems where experimental data is significantly limited.
Angela Lanning +2 more
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Remote Sensing, 2023 Gravity Recovery and Climate Experiment (GRACE)-derived groundwater storage anomalies (GWSA) have been used to highlight groundwater depletion in regional aquifer systems worldwide.
Jianchong Sun +5 more
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The chaos in calibrating crop models: Lessons learned from a multi-model calibration exercise
Environmental Modelling & Software, 2021 Calibration, the estimation of model parameters based on fitting the model to experimental data, is among the first steps in many applications of process-based models and has an important impact on simulated values.
D. Wallach +58 more
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