The absence of aggregated uncertainty measures restricts the assessment of uncertainty in hydrological simulation. In this work, a new composite uncertainty measure is developed to evaluate the complex behaviors of uncertainty existing in hydrologica...
We propose an approach for jointly measuring global macroeconomic uncertainty and bilateral spillovers of uncertainty between countries using a global vector autoregressive (GVAR) model. Over the period 2000Q1–2020Q4, our global index is able t...
Reliable image classification results are crucial for the application of remote sensing images, but the reliability of image classification has received less attention. In particular, the inherent uncertainty of remote sensing images has been disrega...
It is noted that some uncertain variables are independent while others are not. In general, there is a symmetrical relationship between independence and dependence among uncertain variables. The utilization of conditional uncertain measures as well a...
The paper examined the impact of macroeconomic uncertainty on the ten largest subsectors of the Nigerian economy using quarterly data from Q1 1981 to Q4 2023. The rationale behind selecting the subsectors is that these sectors constitute about 89 per...
Reliability analysis and trade-offs between safety and cost with insufficient data represent an inevitable problem during the early stage of structural design. In this paper, efficient uncertainty theory-based reliability analysis and a design method...
In questionnaires, respondents sometimes feel uncertain about which category to choose and may respond randomly. Including uncertainty in the modeling of response behavior aims to obtain more accurate estimates of the impact of explanatory variables...
The COVID-19 pandemic illustrated that intolerance of uncertainty (IU) can hinder problem-solving and lead to avoidance of ambiguous situations. Furthermore, people tend to lack confidence in decisions made in ambiguous contexts. We wanted to investi...
Art theory suggests that the pleasure of art appreciation stems from resolving uncertainty, yet empirical support for this idea remains limited. To address this gap, we conducted three studies (N = 1127), providing empirical evidence for the Aestheti...
The geometrical dimensions and mechanical properties of composite materials exhibit inherent variation and uncertainty in practical engineering. Uncertainties in geometrical dimensions and mechanical properties propagate to the structural performance...
Deterministic flood hazard estimates neglect the inherent uncertainty associated with model estimates and can substantially underestimate flood risk. Monte Carlo simulation (MCS) has been a valuable tool for conducting uncertainty analysis. However,...
A shared commitment to standardising the process of hypothetically reconstructing lost buildings from the past has characterised academic research in recent years and can manifest at various stages of the reconstructive process and with different per...
Analyzing general uncertainty relations one can find that there can exist such pairs of non-commuting observables A and B and such vectors that the lower bound for the product of standard deviations
In the present paper, an uncertainty principle is derived in the quantum wavelet framework. Precisely, a new uncertainty principle for the generalized q-Bessel wavelet transform, based on some q-quantum wavelet, is established. A two-parameters exten...
We examine several measures of uncertainty to make five points. First, equity market traders and executives at nonfinancial firms have shared similar assessments about one-year-ahead uncertainty since the pandemic struck. Both the one-year VIX and ou...
Background and Objectives: The purpose of this study is to enhance the quality of life in elderly patients with lung cancer by understanding relations of uncertainty, appraisal of uncertainty, self-efficacy, and quality of life targeting elderly pati...
In construction planning, decision making has a great impact on final project performance. Hence, it is essential for project managers to assess the construction planning and make informed decisions. However, disproportionately large uncertainties oc...
The qualitative behaviors of uncertainty relations in hydrodynamics are numerically studied for fluids with low Reynolds numbers in
The quantification of uncertainties of computer simulations due to input parameter uncertainties is paramount to assess a model’s credibility. For computationally expensive simulations, this is often feasible only via surrogate models that are learne...
Reliable localization is critical for robot navigation in complex indoor environments. In this paper, we propose an uncertainty-aware localization method that enhances the reliability of localization outputs without modifying the prediction model its...
Greenhouse gas (GHG) emission from electricity generation has been recognized as one of the most significant contributors to global warming. The GHG emission factor of electricity (hereafter, electricity emission factor) can be expressed as a functio...
One of the more technically challenging concepts in quality assurance is the appropriate quantification of the uncertainty of measurement. Consequently, there must be an adequate emphasis on didactic approaches to ascertain that the student is not ju...
For object detection, capturing the scale of uncertainty is as important as accurate localization. Without understanding uncertainties, self-driving vehicles cannot plan a safe path. Many studies have focused on improving object detection, but relati...
As climate change intensifies, climate-related policy instruments have become essential tools for governments to mitigate climate risks. The formulation of such policies typically involves balancing economic growth and ecological goals while ensuring...
Policymakers and portfolio managers pay keen attention to sources of uncertainties that drive asset returns and volatility. The influence of uncertainty on Bitcoin has the potential to drive fluctuations in the entire cryptocurrency market. We invest...
A discharge uncertainty envelope is presented that provides an observation error model for data assimilation (DA) using discharge observations derived from measurement of stage using a rating curve. It uniquely represents the rating curve representat...
Using ensemble forecast experiments generated by the weather research and forecasting model, the forecast uncertainties of intensity and its rapid intensification (RI) induced by the uncertainty occurring in the boundary layer are investigated for Ty...
In open environments, multimodal sentiment analysis (MSA) often suffers from low-quality data and can be disrupted by noise, inherent defects, and outliers. In some cases, unreasonable multimodal fusion methods can perform worse than unimodal methods...
Quantum uncertainty has a tremendous explanatory power. Coherent superposition, quantum equations of motion, entanglement, nonlocal correlations, dynamical nonlocality, contextuality, discord, counterfactual protocols, weak measurements, quantization...
Sensor uncertainty significantly affects the performance of autonomous vehicles (AVs). Sensor uncertainty is predominantly linked to sensor specifications, and because sensor behaviors change dynamically, the machine learning approach is not suitable...
Though an accurate measurement of entropy, or more generally uncertainty, is critical to the success of human–machine teams, the evaluation of the accuracy of such metrics as a probability of machine correctness is often aggregated and not asse...
In real life, indeterminacy and determinacy are symmetric, while indeterminacy is absolute. We are devoted to studying indeterminacy through uncertainty theory. Within the framework of uncertainty theory, uncertain processes are used to model the evo...
Quantitative determination of the uncertainty of a measurement result is the key to assessing the quality and reliability of a measurement process and its result. The comparability of measurement results is ensured by the method for evaluating and ex...
The emergence of a minimal length at the Planck scale is consistent with modern developments in quantum gravity. This is taken into account by transforming the Heisenberg uncertainty principle into the generalized uncertainty principle. Here, the pos...
Forward-looking metrics of uncertainty based on options-implied information should be highly predictive of equity market returns in accordance with asset pricing theory. Empirically, however, the ability of the VIX, for example, to predict returns is...
Cryptocurrency investments are often perceived as uncertain and risky. In this study, we assessed if this is indeed the case, using a sample of seven cryptocurrencies and considered a period that encompassed the first real global shock in the life of...
Various uncertainty analysis methods have been used in various studies to analyze the uncertainty of rainfall-runoff models; however, these methods are difficult to apply immediately as they require a long learning time. In this study, we propose a s...
The simultaneous consideration of a numerical model and of different observations can be achieved using data-assimilation methods. In this contribution, the ensemble Kalman filter (EnKF) is applied to obtain the system-state development and also an e...
Against the background of the rapid development of today’s human society, this article integrates the concept of musical uncertainty through informatization, uses the exploration of dialectics in philosophy to further summarize the informatizat...
Screening and diagnostic tests are applied for the classification of people into diseased and non-diseased populations. Although diagnostic accuracy measures are used to evaluate the correctness of classification in clinical research and practice, th...
This research analyzes the influence of economic policy uncertainty (EPU) on energy consumption driven by tourism in Macau, employing a structural vector autoregression (SVAR) model with sign restrictions. The SVAR model facilitates the identificatio...
This paper extends the canonical small open-economy real-business-cycle model, when considering model uncertainty. Domestic households have multiplier preferences, which leads them to take robust decisions in response to possible model misspecificati...
The credibility of Computational Fluid Dynamics (CFD) has been a topic of debate due to the significant uncertainties inherent in its modeling processes and numerical implementations. Uncertainty Quantification (UQ) offers a scientific framework for...
Different types of uncertainties occur in almost all datasets and are an inherent property of data across different academic disciplines, including digital humanities (DH). In this paper, we address, demonstrate and analyse spatio-temporal uncertaint...
The uncertainty associated with probing the quantum state is expressed as the effective abundance (measure) of possibilities for its collapse. New kinds of uncertainty limits entailed by the quantum description of the physical system arise in this ma...
In most re-identification approaches, embedding vectors are compared to identify the best match for a given query. However, this comparison does not take into account whether the encoded information in the embedding vectors was extracted reliably fro...
This paper investigates the adequacy of radial basis function (RBF)-based models as surrogates in uncertainty quantification (UQ) and CFD shape optimization; for the latter, problems with and without uncertainties are considered. In UQ, these are use...
Uncertainty quantification and sensitivity analysis are essential for improving the modeling and estimation of greenhouse gas emissions in livestock farming to evaluate and reduce the impact of uncertainty in input parameters to model output. The pre...
A key feature of contemporary times is the high degree of complexity that impacts all spheres and aspects of today’s society, particularly within education. This complexity, deriving from a postdigital world in a polycrisis, causes continuous e...
The role of medical diagnosis is essential in patient care and healthcare. Established diagnostic practices typically rely on predetermined clinical criteria and numerical thresholds. In contrast, Bayesian inference provides an advanced framework tha...
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