The balance between water supply and demand is essential for industrial growth, affecting economic, social, and environmental sustainability. Our research employs a Gaussian process regression for demand prediction. Additionally, it takes into accoun...
This contribution exposes the relative uncertainties associated with prediction patterns of landslide susceptibility. The patterns are based on relationships between direct and indirect spatial evidence of landslide occurrences. In a spatial database...
Daily groundwater level is an indicator of groundwater resources. Accurate and reliable groundwater level (GWL) prediction is crucial for groundwater resources management and land subsidence risk assessment. In this study, a representative deep learn...
Multi-criteria decision making (MCDM) refers to methods and processes used to evaluate and prioritize options when multiple criteria are involved. Extensive research conducted in the past has shown that uncertainty is a pervasive challenge in the dec...
Geological models are essential components in various applications. To generate reliable realizations, the geostatistical method focuses on reproducing spatial structures from training images (TIs). Moreover, uncertainty plays an important role in Ea...
Accurate ultra-short-term power interval forecasting for distributed photovoltaic (DPV) systems is crucial for the intra-day operation of distribution networks. However, existing studies still face two major limitations. First, most spatiotemporal fo...
Every experimental measurement is affected by random and/or systematic error sources, causing the measurand to have an associated uncertainty quantified in terms of a confidence interval and confidence level. For high-accuracy spherical near-field an...
Lidar data are regularly used to characterize forest structures. In this study, we determine the effects of three lidar attributes (density, spacing, scanning angle) on the accuracy and the uncertainty of timber merchantable volume estimates of balsa...
Uncertainty analysis of a time-varying ensemble vector field is a challenging topic in geoscience. Due to the complex data structure, the uncertainty of a time-varying ensemble vector field is hard to quantify and analyze. Measuring the differences b...
The presence of the nonstationarity in flow datasets has challenged the flood hazard assessment. Nonstationary tools and evaluation metrics have been proposed to deal with the nonstationarity and guide the infrastructure design and mitigation measure...
Single-valued neutrosophic sets (SVNSs) handling the uncertainties characterized by truth, indeterminacy, and falsity membership degrees, are a more flexible way to capture uncertainty. In this paper, some new types of distance measures, overcoming t...
Since free-space optical links (especially fully photonic ones) are very challenging to accurately align; scanning algorithms are used for the initial search and alignment of the transceivers. The initial alignment aims to intercept the optical beam...
A landslide inventory, after an intense rainfall event in 1998, Southwestern Korea, was collected by digitizing aerial photographs. This left high uncertainty in the inventoried features to be verified by ground truths. To reduce the uncertainty, the...
Partial discharge pattern recognition is a crucial task for assessing the insulation condition of Gas-Insulated Switchgear (GIS). However, the on-site environment presents challenges such as strong electromagnetic interference, leading to acquired si...
This paper proposes an efficient power management approach for the 24 h-ahead optimal maneuver of Mega–scale grid–connected microgrids containing a huge penetration of wind power, dispatchable distributed generation (diesel generator), en...
Omicron, so-called COVID-2, is an emerging variant of COVID-19 which is proved to be the most fatal amongst the other variants such as alpha, beta and gamma variants (
Interaction between variables is often found in statistical models, and it is usually expressed in the model as an additional term when the variables are numeric. However, when the variables are categorical (also known as nominal or qualitative) or m...
The performance of 2D digital imaging systems depends on several factors related with both optical and electronic processing. These concepts have originated standards, which have been conceived for photographic equipment and bi-dimensional scanning s...
Multiple-point geostatistics (MPS) is an established tool for the uncertainty quantification of Earth systems modeling, particularly when dealing with the complexity and heterogeneity of geological data. This study presents a novel pixel-based MPS me...
This study develops a multi-objective fuzzy programming model (MOFPM) that integrates water-footprint accounting with fuzzy chance-constrained programming for multi-objective optimization. It sets differentiated constraints for green-blue-grey water-...
Current studies of complex problem-solving do not commonly evaluate the regulatory role of such personality-based variables as tolerance for uncertainty, risk-readiness, and patterns for coping with decisional conflict. This research aims to establis...
Architecture exists at a moment of instability as economic forces narrow professional agency, as knowledge domains challenge disciplinary boundaries, and as calls for decolonisation and sustainability demand epistemological reorientation. Architectur...
The food system plays a crucial role in mitigating climate change. Even if fossil fuel emissions are halted immediately, current trends in global food systems may prevent the achieving of the Paris Agreement’s climate targets. The high degree o...
Background/Objectives: Parotid ultrasound requires integration of sonographic morphology with clinical context under uncertainty, but conventional agreement and performance metrics provide limited insight into examiner-dependent classification patter...
Parkinson’s disease is a progressive neurodegenerative disorder characterized by motor impairments that significantly affect handwriting and fine motor control. Recent advances in artificial intelligence have enabled the non-invasive analysis o...
Information pertaining to a reservoir’s bathymetry is of utmost significance for water resource sustainability and management. The current study evaluated and compensated the reservoir’s bathymetric patterns established using radial basis...
The integration of Electric Vehicles (EVs) with solar power generation is important for decarbonizing the economy. While electrifying transportation reduces Greenhouse Gas (GHG) emissions, its success depends on ensuring that EVs are charged with cle...
23 February 2021
The impact of individuals’ mobility on the degree of error in estimates of exposure to ambient PM
Uncertainty is at the heart of decision-making processes in most real-world applications. Uncertainty can be broadly categorized into two types: aleatory and epistemic. Aleatory uncertainty describes the variability in the physical system where senso...
The issue of population dataset reliability is of particular importance when it comes to broadening the understanding of spatial structure, pattern and configuration of humans’ geographical location. The aim of the paper was to estimate the rel...
Global agriculture and food system is faced with increasing uncertainty from natural disasters, epidemics, financial crises, and wars. Agricultural trade can provide a powerful supplement to global food security. Eggs have been recognized as the most...
This study introduces a novel mathematical tool for representing imprecise and ambiguous data: the multi-q cubic bipolar fuzzy soft set. Building upon established bipolar fuzzy sets and soft sets, this paper fist defines the concept of multi-q cubic...
The October 7th events precipitated an unprecedented psychological crisis for Israeli families, particularly affecting parents of children with special needs. This empirical study aimed to investigate the psychological factors contributing to parenta...
Unmanned aircraft systems for regional operations are assumed to frequently operate at non-towered airports, where routine integration remains challenging due to limited separation principles and partially observable manned traffic intent. This resea...
One of the most frequent natural perils affecting the world today is flooding, and over the years, flooding has caused a large loss of life and damage to property. Remote sensing technology and satellite imagery derived data are useful in mapping the...
A psychology experiment examining decision-making on a continuum of subjectively equivalent alternatives (directions) revealed that subjects follow a common pattern, giving preference to just a few directions over all others. When restricted experime...
To predict textile quality fluctuation from the perspective of uncertainty factors, first, the reasons and patterns of quality fluctuation in the industrial textile processing were analyzed, and knowledge representation of textile quality attributes...
In this study, an integrated crop–forest system with market approach (ICFM) associated with recovering forest and withdrawing cultivation was developed for confirming regional integrity of economic and ecological objectives under uncertainties....
11 November 2019
There were few studies of individual differences in prognostic decision-making from the psychological point of view; most of them focused on the differences between novices and experts making the prognoses. In this study, we suggested a new task that...
The strain in a fast spinning carbon fiber flywheel rotor is of great interest for condition monitoring, as well as for studying long-term aging effects in the carbon fiber matrix. Optoelectronic strain measurement is a contactless measurement princi...
In this study, we apply a robust optimization approach to a p-center facility location problem under uncertainty. Based on a symmetric interval and a multiple allocation strategy, we use three types of uncertainty sets to formulate the robust problem...
Individual subjects’ ratings neither are metric nor have homogeneous meanings, consequently digital- labeled collections of subjects’ ratings are intrinsically ordinal and categorical. However, in these situations, the literature privileg...
Climate change can exacerbate the occurrence of extreme precipitation events, thereby affecting both the frequency and intensity of rainfall-induced landslides. It is important to study the threat of rainfall-induced landslides under future climate c...
10 December 2018
Restoring natural wetlands with conservation projects is an urgent task for human well-being. This paper introduces the Interval linear programming (ILP) method in wetland restoration projects for the first time and builds an optimization model. The...
Despite many fuzzy time series forecasting (FTSF) models addressing complex temporal patterns and uncertainties in time series data, two limitations persist: they do not treat fuzzy and crisp time series as a unified whole for analyzing nonlinear rel...
This study presents the understanding of temporal dynamics of groundwater-surface water (GW-SW) interaction due to parameter uncertainty by using a physically-based and distributed gridded surface subsurface hydrologic analysis (GSSHA) model combined...
The reliable prediction of future system behavior using sensor data is often hindered by inherent uncertainties, especially in cases where the data undergo gradual changes over time. These uncertainties typically arise from environmental factors or s...
Spatial population distribution is an important determinant of both drivers of regional environmental change and exposure and vulnerability to it. Spatial projections of population must account for changes in aggregate population, urbanization, and s...
Quantification of all types of uncertainty helps to establish reliability in any analysis. This research focuses on uncertainty in two attribute levels of wetland classification and creates visualization tools to guide analysis of spatial uncertainty...
The imperfect effectiveness of seasonal influenza vaccines is often blamed on antigenic mismatch, but even when the match appears good, effectiveness can be surprisingly low. Seasonal influenza vaccines also stand out for their variable effectiveness...
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