Uncertain hypothesis testing for two experts’ empirical data

Wang, Qianqian; Gao, Zhichao; Guo, Haiying

doi:10.1016/j.mcm.2011.10.039

Cited by 36 publications

(17 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, we can use uncertain statistics [21] to determine the uncertainty distribution. With the help of the designed questionnaire survey, the uncertainty distribution can be determined from the expert's experimental data by using the principle of least squares, the method of moments, the Delphi method, and so on [33].…”

Section: Numerical Examplementioning

confidence: 99%

Multidimensional Knapsack Problem Based on Uncertain Measure

Rao

Chen

2017

Scientia Iranica

View full text Add to dashboard Cite

Abstract. The researchers of classical multidimensional knapsack problem have always assumed that the weights, values, and capacities are constant values. However, in the real-life industrial engineering applications, the multidimensional knapsack problem often comes with uncertainty about a lack of information about these parameters. This paper investigates a constrained multidimensional knapsack problem under uncertain environment, in which the relevant parameters are assumed to be uncertain variables. Within the framework of uncertainty theory, two types of uncertain programming models with discount constraints are constructed for the problem with di erent decision criteria, including the expected value criterion and the critical value criterion. Taking full advantage of the operational law for uncertain variables, the proposed models can be transformed into their corresponding deterministic models. After theoretically investigating the properties of the models, we do some numerical experiments. The numerical results illustrate that the proposed models are feasible and e cient for solving the constrained multidimensional knapsack problem with uncertain parameters.

show abstract

Section: Numerical Examplementioning

confidence: 99%

Multidimensional Knapsack Problem Based on Uncertain Measure

Rao

Chen

2017

Scientia Iranica

View full text Add to dashboard Cite

show abstract

“…In addition, Wang and Peng [7] proposed a moment method for estimating the unknown parameters in uncertain statistics in 2010. Also, Wang et al [8] presented uncertain hypothesis testing to detect whether two uncertainty distributions are equal. In order to estimate the uncertainty distribution for an uncertain variable via multiple experts' experimental data, Wang et al [9] proposed a new method based on the uncertain statistic and Delphi method.…”

Section: Introductionmentioning

confidence: 99%

Delphi Method for Estimating Membership Function of Uncertain Set

Guo

Wang

et al. 2016

J. Uncertain. Anal. Appl.

Self Cite

View full text Add to dashboard Cite

Uncertain set is a set-valued function on an uncertainty space, and attempts to model unsharp concepts. Membership function is used to describe the membership degree that a value belongs to the uncertain set. In order to estimate the membership function for an uncertain set via multiple experts' experimental data, this paper presents a new method by the combination of the method of uncertain statistics and Delphi method, and gives an example to verify the method.

show abstract

“…Nowadays, uncertainty theory has become a branch of axiomatic mathematics for modeling human uncertainty, and it has been well developed and applied to uncertain programming [2], uncertain statistics [3], uncertain risk analysis [4], uncertain set [5], uncertain logic [6], uncertain inference [7,8], uncertain process [9], uncertain renewal process [10], uncertain calculus [11], uncertain differential equation [12], uncertain finance [13], and so on. The latest results related to uncertainty theory may be found in [14].…”

Section: Introductionmentioning

confidence: 99%

Maximum-mean uncertain measure

2015

J. Uncertain. Anal. Appl.

View full text Add to dashboard Cite

Uncertain measure, which is used to indicate the degree of belief that an uncertain event may occur, is a set function satisfying the normality, duality, and subadditivity axioms. Although the tools of uncertain measure, uncertainty space, and uncertain variable have been well developed and became the foundations of uncertainty theory, there is no study on how to construct the uncertainty space for an uncertain variable, which seriously hinders the applications of uncertainty theory in practice. In this paper, we propose an expert knowledge-based construction approach for uncertainty space with maximum-mean uncertain measure, which takes the maximum and mean operations on confidence function.

show abstract

Uncertain hypothesis testing for two experts’ empirical data

Cited by 36 publications

References 11 publications

Multidimensional Knapsack Problem Based on Uncertain Measure

Multidimensional Knapsack Problem Based on Uncertain Measure

Delphi Method for Estimating Membership Function of Uncertain Set

Maximum-mean uncertain measure

Contact Info

Product

Resources

About