# Imprecise Probabilities based on Generalized Intervals

@inproceedings{Wang2008ImprecisePB, title={Imprecise Probabilities based on Generalized Intervals}, author={Yan Wang}, year={2008} }

Dierent representations of imprecise probabilities have been proposed, such as evidence theory, coherent behavioral theory, possibility theory, probability bound analysis, F-probabilities, fuzzy probabilities, and clouds. Interval-valued probabilities are used such that uncertainty is distinguished from variability. In this paper, we proposed a new form of imprecise probabilities based on generalized or modal intervals. Generalized intervals are algebraically closed under the Kaucher arithmetic…

## 15 Citations

PROBABILISTIC INFERENCE FOR INTERVAL PROBABILITIES IN DECISION-MAKING PROCESSES

- Computer ScienceENVIRONMENT. TECHNOLOGIES. RESOURCES. Proceedings of the International Scientific and Practical Conference
- 2019

This paper considers one approach to Bayes’ formula based probabilistic inference under interval values of relevant probabilities and shows that it proves to be the best from the viewpoint of the required amount of calculations and visual representation of the results.

Multiscale Uncertainty Quantification Based on a Generalized Hidden Markov Model

- Computer Science
- 2011

A generalized hidden Markov model (GHMM) is proposed to quantify aleatory and epistemic uncertainties simultaneously in multiscale system analysis based on a new imprecise probability theory that has the form of generalized interval.

Multiscale Variability and Uncertainty Quantification Based on a Generalized Multiscale Markov Model

- MathematicsDAC 2010
- 2010

Variability is inherent randomness in systems, whereas uncertainty is due to lack of knowledge. In this paper, a generalized multiscale Markov (GMM) model is proposed to quantify variability and…

Cross-Scale, Cross-Domain Model Validation Based on Generalized Hidden Markov Model and Generalized Interval Bayes' Rule

- Computer Science
- 2013

A recently proposed generalized hidden Markov model (GHMM) is used for cross-scale and cross-domain information fusion under the two types of uncertainties, and the dependency relationships among the observable and hidden state variables at multiple scales and physical domains are captured by generalized interval probability.

Trapezoidal intuitionistic fuzzy number with some arithmetic operations and its application on reliability evaluation

- Computer ScienceInt. J. Math. Oper. Res.
- 2013

Expressions for computing the fuzzy reliability of a series system, parallel system, series-parallel and parallel-series system following TrIFNs have been described and an imprecise failure to start of a truck using TrIFN is taken.

Reliable kinetic Monte Carlo simulation based on random set sampling

- Computer ScienceSoft Comput.
- 2013

A reliable KMC (R-KMC) mechanism is proposed in which sampling is based on random sets instead of random numbers to improve the robustness of KMC results.

Определение остаточной несущей способности железобетонных балок на стадии эксплуатации по критерию прочности арматуры и бетона

- Engineering
- 2015

An experimental theoretical method was considered for estimating the residual load-bearing capacity of an individual reinforced concrete beam at the operational stage according to the criteria of the…

Supply chain performance monitoring using Bayesian network

- BusinessInt. J. Bus. Perform. Supply Chain Model.
- 2013

This research addresses the embedded uncertainty as well as mutual dependency among supply chain performance measures and proposes employing Bayesian network (BN) to monitor them.

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