Uncertainty Analysis - an overview | ScienceDirect Topics
Jul 7, 2018 · Uncertainty analysis aims at quantifying the variability of the output that is due to the variability of the input. The quantification is most often performed by estimating statistical quantities …
Uncertainty Analysis - an overview | ScienceDirect Topics
Abstract Uncertainty analysis consists of quantitatively evaluating uncertainty in model components (input variables, parameters, equations) for a given situation, and deducing an uncertainty …
Uncertainty concepts for integrated modeling - ScienceDirect
Jan 1, 2021 · Uncertainty analysis is essential for identifying robust business strategies and policy interventions (e.g. climate adaptation or mitigation measures). Information on location, type, and …
A review of uncertainty analysis in building energy assessment
Oct 1, 2018 · Therefore, this paper aims to provide a detailed systematic overview of uncertainty analysis in building energy assessment from four aspects: uncertainty data sources, both forward …
Unified uncertainty analysis under probabilistic, evidence, fuzzy and ...
Oct 1, 2019 · The uncertainty analysis of structures generally involves uncertain parameters of different types. In order to derive predictions regarding uncertain structural responses, it is crucial to represent …
Uncertainties in risk analysis: Six levels of treatment
Nov 1, 1996 · Second, six different levels of treatment of uncertainty are presented and discussed in the light of the evolution of the risk management philosophy in the US. Because an in-depth treatment of …
Optimization-Based Approaches to Uncertainty Analysis of Structures ...
Response analysis of structures involving non-probabilistic uncertain parameters can be closely related to optimization. This paper provides a review on optimization-based methods for uncertainty …
Monte-Carlo based uncertainty analysis: Sampling efficiency and ...
Jan 1, 2013 · Sampling-based uncertainty analysis, via Monte Carlo approaches, plays a central role in this characterisation and quantification of uncertainty [3]. In reliability, three methodology levels are …
Performance and uncertainty analysis in deep learning frameworks for ...
Oct 1, 2025 · This analysis included an examination of the importance of different predictors and an assessment of prediction uncertainty through Monte Carlo Dropout techniques. The study reveals …
Describing the uncertainties in experimental results
Jan 1, 1988 · Describing the Single-Sample Uncertainty in a Measurement In single-sample uncertainty analysis, each measurement is assigned three uncertainty values: its zeroth-, first-, and Nth- order …