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Bearing capacity of shallow foundations considering geological uncertainty and soil spatial variability
The bearing capacity of shallow foundation is significantly affected by stratum uncertainty, mainly including geological uncertainty and spatial...
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Analysis of wave resource model spatial uncertainty and its effect on wave energy converter power performance
Wave models used for wave energy resource assessments are subjected to uncertainties, which differ from one location to another over the defined...
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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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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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Quantifying numerical uncertainty in background-oriented schlieren
Our study presents and evaluates a method for computing the numerical uncertainty in background-oriented schlieren (BOS). We use Richardson...
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Uncertainty Analysis in Hydrologic Modelling
Hydrologic modelsHydrologic model differ regarding hydrologic processes, their parameters, inputs and outputs. Consequently, the results of different...
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Catalog-Based Atmosphere Uncertainty Quantification
Due to the ever-increasing space objects population, space situational awareness products and services have become the cornerstone for the safety and...
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Quantifying Uncertainty in Hydrological Drought Index Using Calibrated SWAT Model
The hydrological model requires precise parameter calibration to reflect the basin characteristicsproperly. The optimum parameter values depend...
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Approximating the uncertainty of deep learning reconstruction predictions in single-pixel imaging
Single-pixel imaging (SPI) has the advantages of high-speed acquisition over a broad wavelength range and system compactness. Deep learning (DL) is a...
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Formal Modelling for Multi-Robot Systems Under Uncertainty
Purpose of ReviewTo effectively synthesise and analyse multi-robot behaviour, we require formal task-level models which accurately capture...
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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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Uncertainty-aware correspondence identification for collaborative perception
Correspondence identification is essential for multi-robot collaborative perception, which aims to identify the same objects in order to ensure...
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Efficient and accurate uncertainty quantification in engineering simulations using time-separated stochastic mechanics
A robust method for uncertainty quantification is undeniably leading to a greater certainty in simulation results and more sustainable designs. The...
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Deformation and stability of the seawall, considering the strength uncertainty of cement mixing piles
The cement mixing (CM) pile is a common method of improving soft offshore ground. The strength growth of CM piles under complex conditions is...
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Spatial Indexing of Airplane Trajectory with Open Location Code and Hexagonal Hierarchical Index
Methods of vehicle navigation have been develo** rapidly throughout the long history of aviation. Positioning is an important component of airplane...
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Random matrix theory for robust topology optimization with material uncertainty
This paper presents an efficient computational method for optimal structural design in the presence of uncertain Young’s modulus modeled using...
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Intelligent Recommender System for Spatial Analysis
One of the main applications of recommender systems is the search and decision making in spatial situations. There is an extensive range of applied...
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Uncertainty and Sensitivity Analysis
Uncertainty in engineering systems comes from various sources such as manufacturing imprecision, assembly errors, model variation, and stochastic...
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Uncertainty-guided dual-views for semi-supervised volumetric medical image segmentation
Deep learning has led to tremendous progress in the field of medical artificial intelligence. However, training deep-learning models usually require...
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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...