Статті в журналах з теми "Uncertainty quantification framework"
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Verdonck, H., O. Hach, J. D. Polman, O. Braun, C. Balzani, S. Müller, and J. Rieke. "-An open-source framework for the uncertainty quantification of aeroelastic wind turbine simulation tools." Journal of Physics: Conference Series 2265, no. 4 (May 1, 2022): 042039. http://dx.doi.org/10.1088/1742-6596/2265/4/042039.
Повний текст джерелаWang, Jiajia, Hao Chen, Jing Ma, and Tong Zhang. "Research on application method of uncertainty quantification technology in equipment test identification." MATEC Web of Conferences 336 (2021): 02026. http://dx.doi.org/10.1051/matecconf/202133602026.
Повний текст джерелаZhang, Juan, Junping Yin, and Ruili Wang. "Basic Framework and Main Methods of Uncertainty Quantification." Mathematical Problems in Engineering 2020 (August 31, 2020): 1–18. http://dx.doi.org/10.1155/2020/6068203.
Повний текст джерелаDeVolder, B., J. Glimm, J. W. Grove, Y. Kang, Y. Lee, K. Pao, D. H. Sharp, and K. Ye. "Uncertainty Quantification for Multiscale Simulations1." Journal of Fluids Engineering 124, no. 1 (November 12, 2001): 29–41. http://dx.doi.org/10.1115/1.1445139.
Повний текст джерелаMirzayeva, A., N. A. Slavinskaya, M. Abbasi, J. H. Starcke, W. Li, and M. Frenklach. "Uncertainty Quantification in Chemical Modeling." Eurasian Chemico-Technological Journal 20, no. 1 (March 31, 2018): 33. http://dx.doi.org/10.18321/ectj706.
Повний текст джерелаNeal, Douglas R., Andrea Sciacchitano, Barton L. Smith, and Fulvio Scarano. "Collaborative framework for PIV uncertainty quantification: the experimental database." Measurement Science and Technology 26, no. 7 (June 5, 2015): 074003. http://dx.doi.org/10.1088/0957-0233/26/7/074003.
Повний текст джерелаRasheed, Muhibur, Nathan Clement, Abhishek Bhowmick, and Chandrajit L. Bajaj. "Statistical Framework for Uncertainty Quantification in Computational Molecular Modeling." IEEE/ACM Transactions on Computational Biology and Bioinformatics 16, no. 4 (July 1, 2019): 1154–67. http://dx.doi.org/10.1109/tcbb.2017.2771240.
Повний текст джерелаWestover, M. Brandon, Nathaniel A. Eiseman, Sydney S. Cash, and Matt T. Bianchi. "Information Theoretic Quantification of Diagnostic Uncertainty." Open Medical Informatics Journal 6, no. 1 (December 14, 2012): 36–50. http://dx.doi.org/10.2174/1874431101206010036.
Повний текст джерелаYin, Zhen, Sebastien Strebelle, and Jef Caers. "Automated Monte Carlo-based quantification and updating of geological uncertainty with borehole data (AutoBEL v1.0)." Geoscientific Model Development 13, no. 2 (February 19, 2020): 651–72. http://dx.doi.org/10.5194/gmd-13-651-2020.
Повний текст джерелаNarayan, Akil, and Dongbin Xiu. "Distributional Sensitivity for Uncertainty Quantification." Communications in Computational Physics 10, no. 1 (July 2011): 140–60. http://dx.doi.org/10.4208/cicp.160210.300710a.
Повний текст джерелаPing, Menghao, Xinyu Jia, Costas Papadimitriou, Xu Han, and Chao Jiang. "Statistics-based Bayesian modeling framework for uncertainty quantification and propagation." Mechanical Systems and Signal Processing 174 (July 2022): 109102. http://dx.doi.org/10.1016/j.ymssp.2022.109102.
Повний текст джерелаXie, Wei, Cheng Li, Yuefeng Wu, and Pu Zhang. "A Nonparametric Bayesian Framework for Uncertainty Quantification in Stochastic Simulation." SIAM/ASA Journal on Uncertainty Quantification 9, no. 4 (January 2021): 1527–52. http://dx.doi.org/10.1137/20m1345517.
Повний текст джерелаSaracco, P., and M. G. Pia. "An exact framework for uncertainty quantification in Monte Carlo simulation." Journal of Physics: Conference Series 513, no. 2 (June 11, 2014): 022033. http://dx.doi.org/10.1088/1742-6596/513/2/022033.
Повний текст джерелаSciacchitano, Andrea, Douglas R. Neal, Barton L. Smith, Scott O. Warner, Pavlos P. Vlachos, Bernhard Wieneke, and Fulvio Scarano. "Collaborative framework for PIV uncertainty quantification: comparative assessment of methods." Measurement Science and Technology 26, no. 7 (June 5, 2015): 074004. http://dx.doi.org/10.1088/0957-0233/26/7/074004.
Повний текст джерелаSarrafi, Aral, Zhu Mao, and Michael Shiao. "Uncertainty quantification framework for wavelet transformation of noise-contaminated signals." Measurement 137 (April 2019): 102–15. http://dx.doi.org/10.1016/j.measurement.2019.01.049.
Повний текст джерелаKotteda, V. M. Krushnarao, J. Adam Stephens, William Spotz, Vinod Kumar, and Anitha Kommu. "Uncertainty quantification of fluidized beds using a data-driven framework." Powder Technology 354 (September 2019): 709–18. http://dx.doi.org/10.1016/j.powtec.2019.06.021.
Повний текст джерелаGorodetsky, Alex A., Gianluca Geraci, Michael S. Eldred, and John D. Jakeman. "A generalized approximate control variate framework for multifidelity uncertainty quantification." Journal of Computational Physics 408 (May 2020): 109257. http://dx.doi.org/10.1016/j.jcp.2020.109257.
Повний текст джерелаHu, Mengqi, Yifei Lou, and Xiu Yang. "A General Framework of Rotational Sparse Approximation in Uncertainty Quantification." SIAM/ASA Journal on Uncertainty Quantification 10, no. 4 (October 27, 2022): 1410–34. http://dx.doi.org/10.1137/21m1391602.
Повний текст джерелаKostakis, Filippos, Bradley T. Mallison, and Louis J. Durlofsky. "Multifidelity framework for uncertainty quantification with multiple quantities of interest." Computational Geosciences 24, no. 2 (June 21, 2019): 761–73. http://dx.doi.org/10.1007/s10596-019-9825-1.
Повний текст джерелаShahane, Shantanu, Narayana Aluru, Placid Ferreira, Shiv G. Kapoor, and Surya Pratap Vanka. "Finite volume simulation framework for die casting with uncertainty quantification." Applied Mathematical Modelling 74 (October 2019): 132–50. http://dx.doi.org/10.1016/j.apm.2019.04.045.
Повний текст джерелаGarg, Shailesh, and Souvik Chakraborty. "VB-DeepONet: A Bayesian operator learning framework for uncertainty quantification." Engineering Applications of Artificial Intelligence 118 (February 2023): 105685. http://dx.doi.org/10.1016/j.engappai.2022.105685.
Повний текст джерелаMarepally, Koushik, Yong Su Jung, James Baeder, and Ganesh Vijayakumar. "Uncertainty quantification of wind turbine airfoil aerodynamics with geometric uncertainty." Journal of Physics: Conference Series 2265, no. 4 (May 1, 2022): 042041. http://dx.doi.org/10.1088/1742-6596/2265/4/042041.
Повний текст джерелаNaozuka, Gustavo Taiji, Emanuelle Arantes Paixão, João Vitor Oliveira Silva, Maurício Pessoa da Cunha Menezes, and Regina Cerqueira Almeida. "Model Comparison and Uncertainty Quantification in Tumor Growth." Trends in Computational and Applied Mathematics 22, no. 3 (September 2, 2021): 495–514. http://dx.doi.org/10.5540/tcam.2021.022.03.00495.
Повний текст джерелаSingh, Rishabh, and Jose C. Principe. "Toward a Kernel-Based Uncertainty Decomposition Framework for Data and Models." Neural Computation 33, no. 5 (April 13, 2021): 1164–98. http://dx.doi.org/10.1162/neco_a_01372.
Повний текст джерелаXu, Ting. "Uncertainty, Ignorance and Decision-Making." Amicus Curiae 3, no. 1 (October 27, 2021): 10–32. http://dx.doi.org/10.14296/ac.v3i1.5350.
Повний текст джерелаOh, Min-hwan, Peder Olsen, and Karthikeyan Natesan Ramamurthy. "Crowd Counting with Decomposed Uncertainty." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (April 3, 2020): 11799–806. http://dx.doi.org/10.1609/aaai.v34i07.6852.
Повний текст джерелаChen, Peng, and Nicholas Zabaras. "Adaptive Locally Weighted Projection Regression Method for Uncertainty Quantification." Communications in Computational Physics 14, no. 4 (October 2013): 851–78. http://dx.doi.org/10.4208/cicp.060712.281212a.
Повний текст джерелаKuhn, Thomas, Jakob Dürrwächter, Fabian Meyer, Andrea Beck, Christian Rohde, and Claus-Dieter Munz. "Uncertainty Quantification for Direct Aeroacoustic Simulations of Cavity Flows." Journal of Theoretical and Computational Acoustics 27, no. 01 (March 2019): 1850044. http://dx.doi.org/10.1142/s2591728518500445.
Повний текст джерелаDanquah, Benedikt, Stefan Riedmaier, Yasin Meral, and Markus Lienkamp. "Statistical Validation Framework for Automotive Vehicle Simulations Using Uncertainty Learning." Applied Sciences 11, no. 5 (February 24, 2021): 1983. http://dx.doi.org/10.3390/app11051983.
Повний текст джерелаTalarico, Erick Costa e. Silva, Dario Grana, Leandro Passos de Figueiredo, and Sinesio Pesco. "Uncertainty quantification in seismic facies inversion." GEOPHYSICS 85, no. 4 (June 24, 2020): M43—M56. http://dx.doi.org/10.1190/geo2019-0392.1.
Повний текст джерелаDatar, Makarand, David Gorsich, David Lamb, and Dan Negrut. "A framework for terrain-induced uncertainty quantification in vehicle dynamics simulation." International Journal of Vehicle Systems Modelling and Testing 4, no. 4 (2009): 234. http://dx.doi.org/10.1504/ijvsmt.2009.032018.
Повний текст джерелаNagel, Joseph B., and Bruno Sudret. "A unified framework for multilevel uncertainty quantification in Bayesian inverse problems." Probabilistic Engineering Mechanics 43 (January 2016): 68–84. http://dx.doi.org/10.1016/j.probengmech.2015.09.007.
Повний текст джерелаHilton, Samuel, Federico Cairola, Alessandro Gardi, Roberto Sabatini, Nichakorn Pongsakornsathien, and Neta Ezer. "Uncertainty Quantification for Space Situational Awareness and Traffic Management." Sensors 19, no. 20 (October 9, 2019): 4361. http://dx.doi.org/10.3390/s19204361.
Повний текст джерелаFeng, Jinchao, Joshua L. Lansford, Markos A. Katsoulakis, and Dionisios G. Vlachos. "Explainable and trustworthy artificial intelligence for correctable modeling in chemical sciences." Science Advances 6, no. 42 (October 2020): eabc3204. http://dx.doi.org/10.1126/sciadv.abc3204.
Повний текст джерелаVandenHeuvel, Daniel J., Christopher Drovandi, and Matthew J. Simpson. "Computationally efficient mechanism discovery for cell invasion with uncertainty quantification." PLOS Computational Biology 18, no. 11 (November 16, 2022): e1010599. http://dx.doi.org/10.1371/journal.pcbi.1010599.
Повний текст джерелаJanya-anurak, Chettapong, Thomas Bernard, and Jürgen Beyerer. "Uncertainty quantification of nonlinear distributed parameter systems using generalized polynomial chaos." at - Automatisierungstechnik 67, no. 4 (April 26, 2019): 283–303. http://dx.doi.org/10.1515/auto-2017-0116.
Повний текст джерелаBerger, James O., and Leonard A. Smith. "On the Statistical Formalism of Uncertainty Quantification." Annual Review of Statistics and Its Application 6, no. 1 (March 7, 2019): 433–60. http://dx.doi.org/10.1146/annurev-statistics-030718-105232.
Повний текст джерелаWei, Wei, Jiang Wu, Yang Yu, Tong Niu, and Xinxin Deng. "Uncertainty Quantification Analysis of Wind Power: A Data-Driven Monitoring-Forecasting Framework." IEEE Access 9 (2021): 84403–16. http://dx.doi.org/10.1109/access.2021.3086583.
Повний текст джерелаBuisson, Bertrand, and Djamel Lakehal. "Towards an integrated machine-learning framework for model evaluation and uncertainty quantification." Nuclear Engineering and Design 354 (December 2019): 110197. http://dx.doi.org/10.1016/j.nucengdes.2019.110197.
Повний текст джерелаRicciardi, Denielle E., Oksana A. Chkrebtii, and Stephen R. Niezgoda. "Uncertainty Quantification Accounting for Model Discrepancy Within a Random Effects Bayesian Framework." Integrating Materials and Manufacturing Innovation 9, no. 2 (June 2020): 181–98. http://dx.doi.org/10.1007/s40192-020-00176-2.
Повний текст джерелаJiang, Chen, Zhen Hu, Yixuan Liu, Zissimos P. Mourelatos, David Gorsich, and Paramsothy Jayakumar. "A sequential calibration and validation framework for model uncertainty quantification and reduction." Computer Methods in Applied Mechanics and Engineering 368 (August 2020): 113172. http://dx.doi.org/10.1016/j.cma.2020.113172.
Повний текст джерелаWate, P., M. Iglesias, V. Coors, and D. Robinson. "Framework for emulation and uncertainty quantification of a stochastic building performance simulator." Applied Energy 258 (January 2020): 113759. http://dx.doi.org/10.1016/j.apenergy.2019.113759.
Повний текст джерелаAbbas, Tajammal, and Guido Morgenthal. "Framework for sensitivity and uncertainty quantification in the flutter assessment of bridges." Probabilistic Engineering Mechanics 43 (January 2016): 91–105. http://dx.doi.org/10.1016/j.probengmech.2015.12.007.
Повний текст джерелаRoy, Christopher J., and William L. Oberkampf. "A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing." Computer Methods in Applied Mechanics and Engineering 200, no. 25-28 (June 2011): 2131–44. http://dx.doi.org/10.1016/j.cma.2011.03.016.
Повний текст джерелаPoliannikov, Oleg V., and Alison E. Malcolm. "The effect of velocity uncertainty on migrated reflectors: Improvements from relative-depth imaging." GEOPHYSICS 81, no. 1 (January 1, 2016): S21—S29. http://dx.doi.org/10.1190/geo2014-0604.1.
Повний текст джерелаDu, Hongfei, Emre Barut, and Fang Jin. "Uncertainty Quantification in CNN Through the Bootstrap of Convex Neural Networks." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 13 (May 18, 2021): 12078–85. http://dx.doi.org/10.1609/aaai.v35i13.17434.
Повний текст джерелаTang, Hesheng, Dawei Li, Lixin Deng, and Songtao Xue. "Evidential uncertainty quantification of the Park–Ang damage model in performance based design." Engineering Computations 35, no. 7 (October 1, 2018): 2480–501. http://dx.doi.org/10.1108/ec-11-2017-0466.
Повний текст джерелаSubber, Waad, Sayan Ghosh, Piyush Pandita, Yiming Zhang, and Liping Wang. "Data-Informed Decomposition for Localized Uncertainty Quantification of Dynamical Systems." Vibration 4, no. 1 (December 31, 2020): 49–63. http://dx.doi.org/10.3390/vibration4010004.
Повний текст джерелаDelipei, Gregory Kyriakos, Josselin Garnier, Jean-Charles Le Pallec, and Benoit Normand. "High to Low pellet cladding gap heat transfer modeling methodology in an uncertainty quantification framework for a PWR Rod Ejection Accident with best estimate coupling." EPJ Nuclear Sciences & Technologies 6 (2020): 56. http://dx.doi.org/10.1051/epjn/2020018.
Повний текст джерелаKekez, Toni, Snježana Knezić, and Roko Andričević. "Incorporating Uncertainty of the System Behavior in Flood Risk Assessment—Sava River Case Study." Water 12, no. 10 (September 24, 2020): 2676. http://dx.doi.org/10.3390/w12102676.
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