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Optimizing software release decisions: a TFN-based uncertainty modeling approach
In our contemporary world, where technology is omnipresent and essential to daily life, the reliability of software systems is indispensable....
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Uncertainty and Modeling Principles
In this chapter, the types of uncertainty encountered in any scientific study are presented in terms of objective treatment procedures, especially...
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Uncertainty of concrete strength in shear and flexural behavior of beams using lattice modeling
This paper numerically studied the effect of uncertainty and random distribution of concrete strength in beams failing in shear and flexure using...
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Parameter identification and uncertainty propagation of hydrogel coupled diffusion-deformation using POD-based reduced-order modeling
This study explores reduced-order modeling for analyzing time-dependent diffusion-deformation of hydrogels. The full-order model describing hydrogel...
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Firing Process Modeling of a Soft Recoil Gun Based on Interval Uncertainty Parameter Identification
PurposeThe soft recoil firing technology is an important way to reduce the recoil force of a gun. To further improve the effect of the recoil...
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Probabilistic Modeling and Uncertainty Quantification of Detailed Combustion Simulation for a Swirl Stabilized Spray Burner
To enable risk informed decisions in the simulation-based design and development of novel combustors, uncertainties in the simulation results must be...
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Structural stochastic identification considering modeling uncertainty through sparse grid and similar system analysis
In this paper, a structural identification problem considering modeling uncertainty is investigated, which not only needs to identify the unknown...
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Uncertainty Estimation
Estimating uncertainty is an important part of hydrological data modeling. They offer a measure of confidence in model predictions and aid in...
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Data Preprocessing for Modeling Socioeconomic Systems in View of Uncertainty
The paper addresses the issue of data preparation for contemporary models of socioeconomic systems. Such models mainly focus on the low level of...
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Linear-combined rough vague sets and their three-way decision modeling and uncertainty measurement optimization
Rough sets (RSs) and vague sets (VSs) are fundamental uncertainty methodologies, and their integrated rough vague sets (RVSs) establish a robust...
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Fuzzy Sets Theory and Uncertainty in Mathematical Modeling
This chapter presents a brief discussion about uncertainty based on philosophical principles, mainly from the point of view of the pre-Socratic...
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Uncertainty Budgets
All measurement numbers have finite accuracy, and it is good practice to always state the uncertainty in a measurement. The uncertainty is typically...
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Modeling the Uncertainty of Concurrent Cyclic Processes
Chapter presents a declarative model of a SCCMP that takes into account fuzzy variables. This model is based on the algebra of ordered fuzzy numbers,...
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Design optimization of external engagement cylindrical gear flowmeter under uncertainty
The purpose of this study is to determine the reasonable structural parameters of the external engagement cylindrical gear flowmeter (EGF) under the...
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Model Validation and Uncertainty Quantification, Volume 3 Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics 2023
Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics, 2023,...
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Influence of material parameter variability on the predicted coronary artery biomechanical environment via uncertainty quantification
Central to the clinical adoption of patient-specific modeling strategies is demonstrating that simulation results are reliable and safe. Indeed,...
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Sources of Uncertainty and Membership Functions
This chapter examines the kinds of uncertainties that motivate the use of type-2 fuzzy sets and systems and how data about words can be collected...
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An uncertainty-aware domain adaptive semantic segmentation framework
Semantic segmentation is significant to realize the scene understanding of autonomous driving. Due to the lack of annotated real-world data, the...
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Using Predictive Modeling to Reduce Uncertainty in Managing Industrial Enterprises
Under present conditions of economy management, characterized for rapid IT development, market repurposing and changes in the competitive scope,...
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A surrogate model for uncertainty quantification and global sensitivity analysis of nonlinear large-scale dome structures
Full-scale dome structures intrinsically have numerous sources of irreducible aleatoric uncertainties. A large-scale numerical simulation of the dome...