Results 1 to 10 of about 341,588 (148)

Sensitivity analysis of selection bias: a graphical display by bias-correction index [PDF]

open access: yesPeerJ, 2023
Background In observational studies, how the magnitude of potential selection bias in a sensitivity analysis can be quantified is rarely discussed. The purpose of this study was to develop a sensitivity analysis strategy by using the bias-correction ...
Ping-Chen Chung, I-Feng Lin
doaj   +3 more sources

Age-level bias correction in brain age prediction [PDF]

open access: yesNeuroImage: Clinical, 2023
The predicted age difference (PAD) between an individual’s predicted brain age and chronological age has been commonly viewed as a meaningful phenotype relating to aging and brain diseases.
Biao Zhang   +3 more
doaj   +2 more sources

Investigating statistical bias correction with temporal subsample of the upper Ping River Basin, Thailand

open access: yesJournal of Water and Climate Change, 2021
This study aims to investigate different statistical bias correction techniques to improve the output of a regional climate model (RCM) of daily rainfall for the upper Ping River Basin in Northern Thailand.
Srisunee Wuthiwongtyohtin
doaj   +1 more source

A Simple Bias Correction Scheme in Ocean Data Assimilation

open access: yesJournal of Marine Science and Engineering, 2023
The mode bias is present and time-dependent due to imperfect configurations. Data assimilation is the process by which observations are used to correct the model forecast, and is affected by the bias. How to reduce the bias is an important issue.
Changxiang Yan, Jiang Zhu
doaj   +1 more source

FairLabel: Correcting Bias in Labels

open access: yes2023 IEEE International Conference on Data Mining Workshops (ICDMW), 2023
There are several algorithms for measuring fairness of ML models. A fundamental assumption in these approaches is that the ground truth is fair or unbiased. In real-world datasets, however, the ground truth often contains data that is a result of historical and societal biases and discrimination.
Srinivasan H. Sengamedu, Hien Pham
openaire   +2 more sources

Performance Assessment of Bias Correction Methods for Precipitation and Temperature from CMIP5 Model Simulation

open access: yesApplied Sciences, 2023
Hydrological modeling relies on the inputs provided by General Circulation Model (GCM) data, as this allows researchers to investigate the effects of climate change on water resources. But there is high uncertainty in the climate projections with various
Digambar S. Londhe   +2 more
doaj   +1 more source

Application of a Bias Correction Method to Meteorological Forecast for the Pyeongchang Winter Olympic Games

open access: yes应用气象学报, 2020
The 23rd Winter Olympics Games and the 13th Winter Paralympic Games are held in Pyeongchang, South Korea during 9-25 February 2018 and 8-18 March 2018.
Zhang Yutao, Tong Hua, Sun Jian
doaj   +1 more source

Cross-validation of bias-corrected climate simulations is misleading [PDF]

open access: yesHydrology and Earth System Sciences, 2018
We demonstrate both analytically and with a modelling example that cross-validation of free-running bias-corrected climate change simulations against observations is misleading.
D. Maraun, M. Widmann
doaj   +1 more source

Bias correction of 20 years of IMERG satellite precipitation data over Canada and Alaska

open access: yesJournal of Hydrology: Regional Studies, 2023
Study region: We define two northern study areas: one covering all of Canada and Alaska and a second, smaller subregion surrounding the Peace-Athabasca Delta for testing.
Carolyn Lober   +3 more
doaj   +1 more source

Performance of bias-correction schemes for CMORPH rainfall estimates in the Zambezi River basin [PDF]

open access: yesHydrology and Earth System Sciences, 2019
Satellite rainfall estimates (SREs) are prone to bias as they are indirect derivatives of the visible, infrared, and/or microwave cloud properties, and hence SREs need correction.
W. Gumindoga   +5 more
doaj   +1 more source

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