Relevant bibliographies by topics / Interval uncertainty

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Interval uncertainty'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Interval uncertainty.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Interval uncertainty"

1

Hwang, Yan-An, and Yu-Hsien Liao. "A Resolution Under Interval Uncertainty." Mathematics 13, no. 5 (2025): 762. https://doi.org/10.3390/math13050762.

Full text
Abstract:
Traditional transferable utility (TU) games assume precise real-valued utilities for coalition outcomes, but real-world situations often involve uncertainty or imprecision. Interval TU games extend the classical framework by representing utilities and payoffs as closed intervals, leveraging interval arithmetic to address inherent ambiguities in data. This paper reviews the theoretical foundations of interval TU games and explores allocating solutions under uncertainty. Central to this study is the adaptation of consistency, a fundamental property in game-theoretical resolutions, to the interva
APA, Harvard, Vancouver, ISO, and other styles
2

Kuzmin, Evgeny A. "Logic of Interval Uncertainty." Modern Applied Science 8, no. 5 (2014): 152. http://dx.doi.org/10.5539/mas.v8n5p152.

Full text
Abstract:
The scientific category of uncertainty refers to that group of terms, an interpretation of which is not unambiguous and exact. In non-eliminability of the category soft content barrier there is an objective transition to the interval uncertainty. This research is an attempt to solve the issue of estimating the interval uncertainty based on methods of a logical analysis and a comparison. The approach presented by the paper is opposed to known methods of a mechanical selection of values following a given function. In the course of the research, there has been introduced a concept of the “tenvers
APA, Harvard, Vancouver, ISO, and other styles
3

Huynh, Van-Nam, and Vladik Kreinovich. "Interval/Probabilistic Uncertainty: Editorial." International Journal of Approximate Reasoning 50, no. 8 (2009): 1149–50. http://dx.doi.org/10.1016/j.ijar.2009.06.005.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Alparslan-Gök, S. Zeynep, Silvia Miquel, and Stef H. Tijs. "Cooperation under interval uncertainty." Mathematical Methods of Operations Research 69, no. 1 (2008): 99–109. http://dx.doi.org/10.1007/s00186-008-0211-3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

YAGER, RONALD R., and VLADIK KREINOVICH. "FAIR DIVISION UNDER INTERVAL UNCERTAINTY." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 08, no. 05 (2000): 611–18. http://dx.doi.org/10.1142/s0218488500000423.

Full text
Abstract:
It is often necessary to divide a certain amount of money between n participants, i.e., to assign, to each participant, a certain portionwi≥0 of the whole sum (so that w1+⋯+ wn=1). In some situations, from the fairness requirements, we can uniquely determine these "weights" wi. However, in some other situations, general considerations do not allow us to uniquely determine these weights, we only know the intervals[Formula: see text] of possible fair weights. We show that natural fairness requirements enable us to choose unique weights from these intervals; as a result, we present an algorithm f
APA, Harvard, Vancouver, ISO, and other styles
6

Hend, Dawood. "On Some Algebraic and Order-Theoretic Aspects of Machine Interval Arithmetic." Online Mathematics Journal 01, no. 02 (2019): 1–13. https://doi.org/10.5281/zenodo.2656089.

Full text
Abstract:
Interval arithmetic is a fundamental and reliable mathematical machinery for scientific computing and for addressing uncertainty in general. In order to apply interval mathematics to real life uncertainty problems, one needs a computerized (machine) version thereof, and so, this article is devoted to some mathematical notions concerning the algebraic system of machine interval arithmetic. After formalizing some purely mathematical ingredients of particular importance for the purpose at hand, we give formal characterizations of the algebras of real intervals and machine intervals along with des
APA, Harvard, Vancouver, ISO, and other styles
7

Manring, Noah D. "Measuring Pump Efficiency: Uncertainty Considerations." Journal of Energy Resources Technology 127, no. 4 (2005): 280–84. http://dx.doi.org/10.1115/1.1926311.

Full text
Abstract:
The objective of this paper is to analyze the uncertainty associated with pump efficiency measurements and to determine reasonable confidence intervals for these data. In the past, many industrial sales and some pieces of academic research have been based upon the experimental data of pump efficiencies; yet few have questioned the accuracy of the experimental data and no one has provided a confidence interval which reflects the range of uncertainty in the measurement. In this paper, a method for calculating this confidence interval is presented and it is shown that substantially large confiden
APA, Harvard, Vancouver, ISO, and other styles
8

Severens, Johan L., Theo M. De Boo, and Emmy M. Konst. "UNCERTAINTY OF INCREMENTAL COST-EFFECTIVENESS RATIOS." International Journal of Technology Assessment in Health Care 15, no. 3 (1999): 608–14. http://dx.doi.org/10.1017/s0266462399153157.

Full text
Abstract:
Objective: To compare different methods to estimate the confidence interval of the incremental cost-effectiveness ratio (ICER).Methods: The adequacy of Fieller intervals and three methods for calculating bootstrap intervals are compared based on a simulation of 10,000 trials, using data from one trial.Results: Both Fieller and bootstrap methods lead to unsatisfactory results when the difference in effectiveness is approximately zero. Where this difference is significant, the four methods for calculating confidence intervals for ICER do not give very different results, but Fieller's interval pe
APA, Harvard, Vancouver, ISO, and other styles
9

Entani, Tomoe, and Kazutomi Sugihara. "Uncertainty index based interval assignment by Interval AHP." European Journal of Operational Research 219, no. 2 (2012): 379–85. http://dx.doi.org/10.1016/j.ejor.2012.01.010.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Aminifar, Sadegh, and Arjuna Marzuki. "Uncertainty in Interval Type-2 Fuzzy Systems." Mathematical Problems in Engineering 2013 (2013): 1–16. http://dx.doi.org/10.1155/2013/452780.

Full text
Abstract:
This paper studies uncertainty and its effect on system response displacement. The paper also describes how IT2MFs (interval type-2 membership functions) differentiate from T1MFs (type-1 membership functions) by adding uncertainty. The effect of uncertainty is modeled clearly by introducing a technique that describes how uncertainty causes membership degree reduction and changing the fuzzy word meanings in fuzzy logic controllers (FLCs). Several criteria are discussed for the measurement of the imbalance rate of internal uncertainty and its effect on system behavior. Uncertainty removal is int
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Interval uncertainty"

1

Rekuc, Steven Joseph. "Eliminating Design Alternatives under Interval-Based Uncertainty." Thesis, Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/7218.

Full text
Abstract:
Typically, design is approached as a sequence of decisions in which designers select what they believe to be the best alternative in each decision. While this approach can be used to arrive at a final solution quickly, it is unlikely to result in the most-preferred solution. The reason for this is that all the decisions in the design process are coupled. To determine the most preferred alternative in the current decision, the designer would need to know the outcomes of all future decisions, information that is currently unavailable or indeterminate. Since the designer cannot select a single a
APA, Harvard, Vancouver, ISO, and other styles
2

Pawlik, Amadeusz, and Henry Andersson. "Visualising Interval-Based Simulations." Thesis, Högskolan i Halmstad, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-28592.

Full text
Abstract:
Acumen is a language and tool for modeling and simulating cyber-physical systems. It allows the user to conduct simulations using a technique called rigorous simulation that produces results with explicit error bounds, expressed as intervals. This feature can be useful when designing and testing systems where the reliability of results or taking uncertainty into account is important. Unfortunately, analyzing these simulation results can be difficult, as Acumen supports only two ways of presenting them: raw data tables and 2D-plots. These views of the data make certain kinds of analysis cumbers
APA, Harvard, Vancouver, ISO, and other styles
3

Xiao, Naijia. "Interval finite element approach for inverse problems under uncertainty." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54336.

Full text
Abstract:
Inverse problems aim at estimating the unknown excitations or properties of a physical system based on available measurements of the system response. For example, wave tomography is used in geophysics for seismic waveform inversion; in biomedical engineering, optical tomography is used to detect breast cancer tissue; in structural engineering, inversion techniques are used for health monitoring and damage detection in structural safety evaluation. Inverse solvers depend on the type of measurement data the unknown parameters to be estimated. The work in this thesis focuses on structural paramet
APA, Harvard, Vancouver, ISO, and other styles
4

Rocco, Claudio. "Techniques to analyse system performance under uncertainty." Thesis, Robert Gordon University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.313442.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Hall, James William. "Uncertainty management for coastal defence systems." Thesis, University of Bristol, 1999. http://hdl.handle.net/1983/9b1c8d07-24f0-48b9-bb7f-73d8d7c40ae6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Shinde, Krushna. "Interval uncertainty method to treat inconsistent measurements in inverse problems." Thesis, Compiègne, 2021. http://www.theses.fr/2021COMP2594.

Full text
Abstract:
Le problème inverse consiste à trouver les valeurs des paramètres d’un modèle physique à partir d’un ensemble de mesures. Dans les problèmes de génie mécanique, la caractérisation du comportement des matériaux nécessite une méthode inverse pour identifier les paramètres des matériaux. Le problème d’identification déterministe est généralement sensible aux données, et une façon de résoudre ce problème est de prendre en compte les incertitudes dans les données. Bien que plusieurs de ces méthodes existent dans la littérature, la plupart d’entre elles utilisent la minimisation des moindres carrés
APA, Harvard, Vancouver, ISO, and other styles
7

Gyekye, Kwame Boakye. "Interval-valued Uncertainty Capability Indices with South African Industrial Applications." Master's thesis, University of Cape Town, 2014. http://hdl.handle.net/11427/12947.

Full text
Abstract:
Includes bibliographical references.<br>Since the advent of statistical quality control and process capability analysis, its study and application has gained tremendous attention both in academia and industry. This attention is due to its ability to describe the capability of a complex process adequately, simply (i.e. using a unitless index) and also in some instances to compare different manufacturing processes. However, the application of statistical quality control has come under intense criticism, notably in one car manufacturing industry where the actual number of non-conforming units con
APA, Harvard, Vancouver, ISO, and other styles
8

Eyoh, Imo. "Interval type-2 Atanassov-intuitionistic fuzzy logic for uncertainty modelling." Thesis, University of Nottingham, 2018. http://eprints.nottingham.ac.uk/51441/.

Full text
Abstract:
This thesis investigates a new paradigm for uncertainty modelling by employing a new class of type-2 fuzzy logic system that utilises fuzzy sets with membership and non-membership functions that are intervals. Fuzzy logic systems, employing type-1 fuzzy sets, that mark a shift from computing with numbers towards computing with words have made remarkable impacts in the field of artificial intelligence. Fuzzy logic systems of type-2, a generalisation of type-1 fuzzy logic systems that utilise type-2 fuzzy sets, have created tremendous advances in uncertainty modelling. The key feature of the typ
APA, Harvard, Vancouver, ISO, and other styles
9

Saad, Aya Hassan [Verfasser]. "CDF-intervals: a probabilistic interval constraint framework to reason about data with uncertainty / Aya Hassan Saad." Ulm : Universität Ulm, 2016. http://d-nb.info/1101578289/34.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Zhang, Hao. "Nondeterministic Linear Static Finite Element Analysis: An Interval Approach." Diss., Available online, Georgia Institute of Technology, 2005, 2005. http://etd.gatech.edu/theses/available/etd-08232005-020145/.

Full text
Abstract:
Thesis (Ph. D.)--Civil and Environmental Engineering, Georgia Institute of Technology, 2006.<br>White, Donald, Committee Member ; Will, Kenneth, Committee Member ; Zureick, Abdul Hamid, Committee Member ; Hodges, Dewey, Committee Member ; Muhanna, Rafi, Committee Chair ; Haj-Ali, Rami, Committee Member.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Interval uncertainty"

1

Huynh, Van-Nam, Yoshiteru Nakamori, Hiroakira Ono, Jonathan Lawry, Vkladik Kreinovich, and Hung T. Nguyen, eds. Interval / Probabilistic Uncertainty and Non-Classical Logics. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-77664-2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Nguyen, Hung T., Vladik Kreinovich, Berlin Wu, and Gang Xiang. Computing Statistics under Interval and Fuzzy Uncertainty. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24905-1.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Van-Nam, Huynh, ed. Interval/probabilistic uncertainty and non-classical logics. Springer, 2008.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Pękala, Barbara. Uncertainty Data in Interval-Valued Fuzzy Set Theory. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-93910-0.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Pownuk, Andrew, and Vladik Kreinovich. Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91026-0.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Nguyen, Hung T. Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering. Springer-Verlag Berlin Heidelberg, 2012.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Servin, Christian, and Vladik Kreinovich. Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12628-9.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Hans, Bandemer, ed. Modelling uncertain data. Akademie Verlag, 1992.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

J, Goossens L. H., U.S. Nuclear Regulatory Commission. Office of Nuclear Regulatory Research. Division of Systems Technology., and Sandia National Laboratories, eds. Probabilistic accident consequence uncertainty analysis: Uncertainty assessment for internal dosimetry. Division of Systems Technology, Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission, 1998.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

J, Goossens L. H., U.S. Nuclear Regulatory Commission. Office of Nuclear Regulatory Research. Division of Systems Technology., and Commission of the European Communities., eds. Probabilistic accident consequence uncertainty analysis: Uncertainty assessment for internal dosimetry. U.S. Nuclear Regulatory Commission, 1998.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Interval uncertainty"

1

Tucker, Warwick. "Interval Methods." In Uncertainty in Biology. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21296-8_8.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Qin, Zhongfeng. "Interval Mean-Semiabsolute Deviation Model." In Uncertainty and Operations Research. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1810-7_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Ben Zakour, Asma, Sofian Maabout, Mohamed Mosbah, and Marc Sistiaga. "Uncertainty Interval Temporal Sequences Extraction." In Information Systems, Technology and Management. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29166-1_23.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Bargiela, Andrzej. "Interval and Ellipsoidal Uncertainty Models." In Granular Computing. Physica-Verlag HD, 2001. http://dx.doi.org/10.1007/978-3-7908-1823-9_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Nguyen, Hung T., Vladik Kreinovich, Berlin Wu, and Gang Xiang. "Computing Mean under Interval Uncertainty." In Computing Statistics under Interval and Fuzzy Uncertainty. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24905-1_12.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Nguyen, Hung T., Vladik Kreinovich, Berlin Wu, and Gang Xiang. "Computing Covariance under Interval Uncertainty." In Computing Statistics under Interval and Fuzzy Uncertainty. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24905-1_21.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Nguyen, Hung T., Vladik Kreinovich, Berlin Wu, and Gang Xiang. "Computing Correlation under Interval Uncertainty." In Computing Statistics under Interval and Fuzzy Uncertainty. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24905-1_22.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Ruspini, Enrique H. "Approximate inference and interval probabilities." In Uncertainty in Knowledge-Based Systems. Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/3-540-18579-8_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Kreinovich, Vladik, Anatoly Lakeyev, Jiří Rohn, and Patrick Kahl. "Non-Interval Uncertainty I: Ellipsoid Uncertainty and its Generalizations." In Computational Complexity and Feasibility of Data Processing and Interval Computations. Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-2793-7_23.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Kreinovich, Vladik, Anatoly Lakeyev, Jiří Rohn, and Patrick Kahl. "Non-Interval Uncertainty II: Multi-Intervals and Their Generalizations." In Computational Complexity and Feasibility of Data Processing and Interval Computations. Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-2793-7_24.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Interval uncertainty"

1

Ferah, Mehmet Ali, and Tufan Kumbasar. "Introducing Interval Neural Networks for Uncertainty-Aware System Identification." In 2025 7th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (ICHORA). IEEE, 2025. https://doi.org/10.1109/ichora65333.2025.11017048.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Jiang, Jesse, Ye Zhao, and Samuel Coogan. "Local-Global Interval MDPs for Efficient Motion Planning with Learnable Uncertainty." In 2024 American Control Conference (ACC). IEEE, 2024. http://dx.doi.org/10.23919/acc60939.2024.10644660.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Choi, Hyungjin, Ryan Elliott, Dhruva Venkat, and Dan Trudnowski. "Security Constrained Uncertainty Interval Estimation using Sensitivity Trajectories in Dynamical Systems." In 2024 American Control Conference (ACC). IEEE, 2024. http://dx.doi.org/10.23919/acc60939.2024.10644345.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Louifi, Abdelhalim, Abdelmalek Kouadri, Mohamed Faouzi Harkat, Abderazak Bensmail, Majdi Mansouri, and Hazem Nounou. "Uncertainty Quantification Kernel PCA: Enhancing Fault Detection in Interval-Valued Data." In 2024 10th International Conference on Control, Decision and Information Technologies (CoDIT). IEEE, 2024. http://dx.doi.org/10.1109/codit62066.2024.10708257.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Lynn, Walt. "Azimuthal interval velocity uncertainty." In SEG Technical Program Expanded Abstracts 2011. Society of Exploration Geophysicists, 2011. http://dx.doi.org/10.1190/1.3627776.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Du, Xiaoping, and Harsheel Shah. "Quantifying Model Uncertainty Using Measurement Uncertainty Standards." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-47865.

Full text
Abstract:
There is always a deviation between a model prediction and the reality that the model intends to represent. The deviation is largely caused by the model uncertainty due to ignorance, assumptions, simplification, and other sources of lack of knowledge. Quantifying model uncertainty is a vital task and requires the comparison between model prediction and observation. This exercise is generally computationally intensive on the prediction side and costly on the experimentation side. In this work, a new methodology is proposed to provide an alternative implementation of model uncertainty quantifica
APA, Harvard, Vancouver, ISO, and other styles
7

Wang, Yan. "Independence in Generalized Interval Probability." In First International Symposium on Uncertainty Modeling and Analysis and Management (ICVRAM 2011); and Fifth International Symposium on Uncertainty Modeling and Anaylsis (ISUMA). American Society of Civil Engineers, 2011. http://dx.doi.org/10.1061/41170(400)5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Lew, Jiann-Shiun, and Kyong B. Lim. "Order Reduction of Identified Interval Model for Systems With Uncertain Parameters." In ASME 1997 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/detc97/vib-4244.

Full text
Abstract:
Abstract This paper addresses the issue of modeling a system with parametric uncertainty via a reduced-order interval model. A system with parametric uncertainty is represented by intervals of transfer function coefficients obtained directly from time-domain response data. An approach based on the sensitivity of a performance specification to the identified uncertain parameters is developed for efficiently analyzing the identified interval model. This approach can significantly reduce the computational effort required by interval system techniques and hence simplify its robust control design.
APA, Harvard, Vancouver, ISO, and other styles
9

Zhang, Yanjun, Tingting Xia, and Mian Li. "Robust Optimization With Mixed Interval and Probabilistic Parameter Uncertainties, Model Uncertainty, and Metamodeling Uncertainty." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-97495.

Full text
Abstract:
Abstract Various types of uncertainties, such as parameter uncertainty, model uncertainty, metamodeling uncertainty may lead to low robustness. Parameter uncertainty can be either epistemic or aleatory in physical systems, which have been widely represented by intervals and probability distributions respectively. Model uncertainty is formally defined as the difference between the true value of the real-world process and the code output of the simulation model at the same value of inputs. Additionally, metamodeling uncertainty is introduced due to the usage of metamodels. To reduce the effects
APA, Harvard, Vancouver, ISO, and other styles
10

Yoo, David, and Jiong Tang. "Vibration-Based Structural Damage Identification Under Interval Uncertainty." In ASME 2016 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/dscc2016-9874.

Full text
Abstract:
Identifying damages in mechanical structures in advance is essential part of preventing catastrophic losses. Among several non-destructive methods, the vibration-based method, which utilizes global characteristics of the structures, has several advantages such as not requiring prior information on possible damage location and physical access to it. In the meantime, the mechanical structures are inevitably subject to uncertainties, whose distribution is often unknown in practical situations due to such as limited amount of available data. Uncertainties are treated as interval uncertainty in suc
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Interval uncertainty"

1

Kreinovich, Vladik, William Louis Oberkampf, Lev Ginzburg, Scott Ferson, and Janos Hajagos. Experimental uncertainty estimation and statistics for data having interval uncertainty. Office of Scientific and Technical Information (OSTI), 2007. http://dx.doi.org/10.2172/910198.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Zio, Enrico, and Nicola Pedroni. Literature review of methods for representing uncertainty. Fondation pour une culture de sécurité industrielle, 2013. http://dx.doi.org/10.57071/124ure.

Full text
Abstract:
This document provides a critical review of different frameworks for uncertainty analysis, in a risk analysis context: classical probabilistic analysis, imprecise probability (interval analysis), probability bound analysis, evidence theory, and possibility theory. The driver of the critical analysis is the decision-making process and the need to feed it with representative information derived from the risk assessment, to robustly support the decision. Technical details of the different frameworks are exposed only to the extent necessary to analyze and judge how these contribute to the communic
APA, Harvard, Vancouver, ISO, and other styles
3

Johra, Hicham. Simple uncertainty budget and assessment with the Kragten method: Examples for building physics. Department of the Built Environment, 2024. http://dx.doi.org/10.54337/aau633631860.

Full text
Abstract:
The aim of this lecture note is to present and exemplify the Kragten method to calculate the combined uncertainty (uncertainty budget) of a measurand from the standard uncertainty estimates of individual inputs of that measurand, and the mathematical formulation of that measurand. If these two elements are not available, the Kragten method cannot be applied. The method also provides sensitivity (significance) assessment of the different components (inputs) in the combined uncertainty budget. The Kragten method for uncertainty calculation is very simple yet a robust and accurate alternative to
APA, Harvard, Vancouver, ISO, and other styles
4

Goossens, L. H. J., B. C. P. Kraan, R. M. Cooke, J. D. Harrison, F. T. Harper, and S. C. Hora. Probabilistic accident consequence uncertainty analysis -- Uncertainty assessment for internal dosimetry. Volume 2: Appendices. Office of Scientific and Technical Information (OSTI), 1998. http://dx.doi.org/10.2172/291005.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Goossens, L. H. J., B. C. P. Kraan, R. M. Cooke, J. D. Harrison, F. T. Harper, and S. C. Hora. Probabilistic accident consequence uncertainty analysis -- Uncertainty assessment for internal dosimetry. Volume 1: Main report. Office of Scientific and Technical Information (OSTI), 1998. http://dx.doi.org/10.2172/291004.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Desjardins. L52204 Framework for the Optimization of Inspection Intervals. Pipeline Research Council International, Inc. (PRCI), 2004. http://dx.doi.org/10.55274/r0011352.

Full text
Abstract:
The goal of this project is to develop a methodology to find the optimal inspection timing of pipelines carrying hazardous materials. The four principle parameters affecting the need for inspection are: - Anomaly severity - Deterioration rate Limit state - Consequences of failure In addition to these parameters, considered in this research, uncertainty needs to be understood and accounted for. Knowledge of each of the above parameters is limited by various factors. Morrison has chosen to approach this uncertainty with a probabilistic method that leads to a risk and reliability solution. As app
APA, Harvard, Vancouver, ISO, and other styles
7

Holland, Darren, and Nazmina Mahmoudzadeh. Foodborne Disease Estimates for the United Kingdom in 2018. Food Standards Agency, 2020. http://dx.doi.org/10.46756/sci.fsa.squ824.

Full text
Abstract:
In February 2020 the FSA published two reports which produced new estimates of foodborne norovirus cases. These were the ‘Norovirus Attribution Study’ (NoVAS study) (O’Brien et al., 2020) and the accompanying internal FSA technical review ‘Technical Report: Review of Quantitative Risk Assessment of foodborne norovirus transmission’ (NoVAS model review), (Food Standards Agency, 2020). The NoVAS study produced a Quantitative Microbiological Risk Assessment model (QMRA) to estimate foodborne norovirus. The NoVAS model review considered the impact of using alternative assumptions and other data so
APA, Harvard, Vancouver, ISO, and other styles
8

Shieh, Lueang-San, and Guanrong Chen. Interval Method for Analysis and Design of Hybrid Uncertain Systems. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada398312.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Diakonova, Marina, Corinna Ghirelli, Luis Molina, and Javier J. Pérez. The economic impact of conflict-related and policy uncertainty shocks: the case of Russia. Banco de España, 2022. http://dx.doi.org/10.53479/23707.

Full text
Abstract:
We show how policy uncertainty and conflict-related shocks impact the dynamics of economic activity (GDP) in Russia. We use alternative indicators of “conflict”, relating to specific aspects of this general concept: geopolitical risk, social unrest, outbreaks of political violence and escalations into internal armed conflict. For policy uncertainty we employ the workhorse economic policy uncertainty (EPU) indicator. We use two distinct but complementary empirical approaches. The first is based on a time series mixed-frequency forecasting model. We show that the indicators provide useful inform
APA, Harvard, Vancouver, ISO, and other styles
10

He, Xihua. PR-015-113601-R02 Validation of Internal Corrosion Threat Models for Dry Natural Gas Pipelines. Pipeline Research Council International, Inc. (PRCI), 2015. http://dx.doi.org/10.55274/r0010914.

Full text
Abstract:
This report documents the verification and validation (of the probabilistic models developed previously to predict internal corrosion (IC) threats in nominally dry natural gas pipelines. Model uncertainty quantification showed that "low temperature, high pressure" posed the greatest IC threat. To validate the model, actual measurements were compared to model-predicted wall loss. The comparison included information from an IC failure, investigated by the National Transportation Safety Board (NTSB), with in-line inspection (ILI) data sets from five pipeline operators. Two of the pipeline operato
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Interval uncertainty' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography