Model uncertainty – parameter uncertainty versus conceptual models
Water Science and Technology, 2005 Uncertainties in model structures have been recognised often to be the main source of uncertainty in predictive model simulations. Despite this knowledge, uncertainty studies are traditionally limited to a single deterministic model and the uncertainty addressed by a parameter uncertainty study.
A L, Højberg, J C, Refsgaard
openaire +2 more sources
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data [PDF]
Journal of Computational Physics, 2019 Surrogate modeling and uncertainty quantification tasks for PDE systems are most often considered as supervised learning problems where input and output data pairs are used for training.
Yinhao Zhu +3 more
semanticscholar +1 more source
Quantified Uncertainty in Thermodynamic Modeling for Materials Design [PDF]
, 2019 Phase fractions, compositions and energies of the stable phases as a function of macroscopic composition, temperature, and pressure (X-T-P) are the principle correlations needed for the design of new materials and improvement of existing materials.
Bocklund, Brandon J +4 more
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A Neutrosophic Reflexive Disruption Evolutionary Integral Model for Evaluating the Quality of University Online Education Interactive Platforms Under Teaching Resource Integration [PDF]
Neutrosophic Sets and SystemsThis paper presents a new mathematical model for evaluating the quality of university online education platforms, especially in environments where multiple teaching resources are being integrated.
Jingjie Li, Xiaoying Zhu
doaj +1 more source
A Novel Neutrosophic Integral Framework for Classroom Teaching Quality Analysis in Children’s Dance Aesthetic Education [PDF]
Neutrosophic Sets and SystemsEvaluating classroom teaching quality in children’s dance aesthetic education is challenging due to uncertainty, subjective judgment, and multiple viewpoints.
Xinxin Li
doaj +1 more source
UNCERTAINTY MODELING AND INTERPRETABILITY IN CONVOLUTIONAL NEURAL NETWORKS FOR POLYP SEGMENTATION [PDF]
International Workshop on Machine Learning for Signal Processing, 2018 Convolutional Neural Networks (CNNs) are propelling advances in a range of different computer vision tasks such as object detection and object segmentation.
Kristoffer Wickstrøm +2 more
semanticscholar +1 more source
A Refined Neutrosophic Over/Under Probability Model with Off-Norm Operators for Evaluating the Efficiency of AI-Based Digital Tools in Korean Language Teaching [PDF]
Neutrosophic Sets and SystemsThis paper presents a new mathematical model based on refined neutrosophic theory to evaluate the efficiency of AI-based digital tools in Korean language teaching.
Ting Yu
doaj +1 more source
Evaluation of touch trigger probe measurement uncertainty using FEA [PDF]
, 2006 Evaluation of measurement uncertainty is an essential subject in dimensional measurement. It has also become a dominant issue in coordinate measuring machine (CMM) even though its machine performance has been well accepted by many users.
Jones, BE, Salleh, MR, Yang, QP
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Green Supply Chain Management Capability Evaluation Using Neutrosophic TwoFold Algebra Decision Model [PDF]
Neutrosophic Sets and SystemsGreen Supply Chain Management (GSCM) has become a priority for organizations striving to improve sustainability while maintaining competitiveness. However, assessing GSCM capabilities is complicated by the uncertain, ambiguous, and interrelated nature of
Hui Wang
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IEEE transactions on industrial electronics (1982. Print), 2019 The remaining useful life (RUL) of transformer insulation paper is largely determined by the winding hot-spot temperature (HST). Frequently the HST is not directly monitored and it is inferred from other measurements.
J. Aizpurua +5 more
semanticscholar +1 more source