Characterising uncertainties in human exposure modelling through the Random Sampling-High Dimensional Model Representation (RS-HDMR) methodology

Sheng-Wei Wang; Panos G. Georgopoulos; Genyuan Li; Herschel Rabitz

doi:10.1504/ijram.2005.007179

Characterising uncertainties in human exposure modelling through the Random Sampling-High Dimensional Model Representation (RS-HDMR) methodology

International Journal of Risk Assessment and Management ◽

10.1504/ijram.2005.007179 ◽

2005 ◽

Vol 5 (2/3/4) ◽

pp. 387 ◽

Cited By ~ 6

Author(s):

Sheng-Wei Wang ◽

Panos G. Georgopoulos ◽

Genyuan Li ◽

Herschel Rabitz

Keyword(s):

Random Sampling ◽

Human Exposure ◽

Model Representation ◽

High Dimensional ◽

High Dimensional Model Representation ◽

Dimensional Model

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Random Sampling High Dimensional Model Representation Gaussian Process Regression (RS-HDMR-GPR) for representing multidimensional functions with machine-learned lower-dimensional terms allowing insight with a general method

Computer Physics Communications ◽

10.1016/j.cpc.2021.108220 ◽

2021 ◽

pp. 108220

Author(s):

Owen Ren ◽

Mohamed Ali Boussaidi ◽

Dmitry Voytsekhovsky ◽

Manabu Ihara ◽

Sergei Manzhos

Keyword(s):

Gaussian Process ◽

Random Sampling ◽

Gaussian Process Regression ◽

Model Representation ◽

High Dimensional ◽

High Dimensional Model Representation ◽

Dimensional Model ◽

Lower Dimensional ◽

General Method

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A random-sampling high dimensional model representation neural network for building potential energy surfaces

The Journal of Chemical Physics ◽

10.1063/1.2336223 ◽

2006 ◽

Vol 125 (8) ◽

pp. 084109 ◽

Cited By ~ 154

Author(s):

Sergei Manzhos ◽

Tucker Carrington

Keyword(s):

Neural Network ◽

Potential Energy ◽

Random Sampling ◽

Potential Energy Surfaces ◽

Model Representation ◽

High Dimensional ◽

High Dimensional Model Representation ◽

Dimensional Model ◽

Energy Surfaces

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Nonlinear bionetwork structure inference using the random sampling-high dimensional model representation (RS-HDMR) algorithm

10.1109/iembs.2009.5333798 ◽

2009 ◽

Cited By ~ 2

Author(s):

M. Miller ◽

Xiaojiang Feng ◽

Genyuan Li ◽

H. Rabitz

Keyword(s):

Random Sampling ◽

Model Representation ◽

High Dimensional ◽

High Dimensional Model Representation ◽

Dimensional Model

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Regularized random-sampling high dimensional model representation (RS-HDMR)

Journal of Mathematical Chemistry ◽

10.1007/s10910-007-9250-x ◽

2007 ◽

Vol 43 (3) ◽

pp. 1207-1232 ◽

Cited By ~ 44

Author(s):

Genyuan Li ◽

Herschel Rabitz ◽

Jishan Hu ◽

Zheng Chen ◽

Yiguang Ju

Keyword(s):

Random Sampling ◽

Model Representation ◽

High Dimensional ◽

High Dimensional Model Representation ◽

Dimensional Model

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Random Sampling-High Dimensional Model Representation (RS-HDMR) and Orthogonality of Its Different Order Component Functions

The Journal of Physical Chemistry A ◽

10.1021/jp054148m ◽

2006 ◽

Vol 110 (7) ◽

pp. 2474-2485 ◽

Cited By ~ 113

Author(s):

Genyuan Li ◽

Jishan Hu ◽

Sheng-Wei Wang ◽

Panos G. Georgopoulos ◽

Jacqueline Schoendorf ◽

...

Keyword(s):

Random Sampling ◽

Model Representation ◽

High Dimensional ◽

High Dimensional Model Representation ◽

Dimensional Model ◽

Order Component ◽

Different Order

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Structural damage identification: A random sampling-high dimensional model representation approach

Advances in Structural Engineering ◽

10.1177/1369433216630370 ◽

2016 ◽

Vol 19 (6) ◽

pp. 908-927 ◽

Cited By ~ 32

Author(s):

Tanmoy Mukhopadhyay ◽

Rajib Chowdhury ◽

Anupam Chakrabarti

Keyword(s):

Random Sampling ◽

Structural Damage ◽

Damage Identification ◽

Model Representation ◽

High Dimensional ◽

High Dimensional Model Representation ◽

Dimensional Model ◽

Structural Damage Identification

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Global sensitivity analysis of riveting parameters based on a random sampling-high dimensional model representation

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-021-06593-7 ◽

2021 ◽

Vol 113 (1-2) ◽

pp. 465-472

Author(s):

Junqing Yin ◽

Jinyu Gu ◽

Yongdang Chen ◽

Feng Zhang

Keyword(s):

Sensitivity Analysis ◽

Random Sampling ◽

Global Sensitivity Analysis ◽

Model Representation ◽

High Dimensional ◽

High Dimensional Model Representation ◽

Dimensional Model ◽

Global Sensitivity

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Global Sensitivity Analysis of the Regional Atmospheric Chemical Mechanism: An Application of Random Sampling-High Dimensional Model Representation to Urban Oxidation Chemistry

Environmental Science & Technology ◽

10.1021/es301565w ◽

2012 ◽

Vol 46 (20) ◽

pp. 11162-11170 ◽

Cited By ~ 11

Author(s):

Shuang Chen ◽

William H. Brune ◽

Oluwayemisi O. Oluwole ◽

Charles E. Kolb ◽

Fred Bacon ◽

...

Keyword(s):

Sensitivity Analysis ◽

Random Sampling ◽

Global Sensitivity Analysis ◽

Model Representation ◽

Chemical Mechanism ◽

High Dimensional ◽

High Dimensional Model Representation ◽

Dimensional Model ◽

Global Sensitivity ◽

Oxidation Chemistry

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Random Sampling−High Dimensional Model Representation (RS−HDMR) with Nonuniformly Distributed Variables: Application to an Integrated Multimedia/Multipathway Exposure and Dose Model for Trichloroethylene

The Journal of Physical Chemistry A ◽

10.1021/jp022500f ◽

2003 ◽

Vol 107 (23) ◽

pp. 4707-4716 ◽

Cited By ~ 51

Author(s):

Sheng-Wei Wang ◽

Panos G. Georgopoulos ◽

Genyuan Li ◽

Herschel Rabitz

Keyword(s):

Random Sampling ◽

Model Representation ◽

High Dimensional ◽

High Dimensional Model Representation ◽

Dimensional Model ◽

Dose Model

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Structural damage identification of bridge using high dimensional model representation

International Journal for Computational Methods in Engineering Science and Mechanics ◽

10.1080/15502287.2020.1861128 ◽

2020 ◽

pp. 1-13

Author(s):

B. O. Naveen ◽

A. S. Balu

Keyword(s):

Structural Damage ◽

Damage Identification ◽

Model Representation ◽

High Dimensional ◽

High Dimensional Model Representation ◽

Dimensional Model ◽

Structural Damage Identification

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