A modeling and analysis strategy of constellation availability using on-orbit and ground added launch backup and its application in the reliability design for a remote sensing satellite

Zhang, Hua; Meng, Debiao; Zong, Yiyan; Wang, Fang; Xin, Tailin

doi:10.1177/1687814018769783

Cited by 15 publications

(10 citation statements)

References 16 publications

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“…Uncertainty exist in the real world and uncertainty modeling has many math tools, such as fuzzy sets, probabilistic model, Z numbers, IFS, D numbers, entropy function, decision tree, pattern recognition, network analysis, and so on. D‐S evidence theory is a hot topic in decision theory, and the theory has a wide range of applications in many fields.…”

Section: Preliminariesmentioning

confidence: 99%

An association coefficient of a belief function and its application in a target recognition system

Pan

Deng

2019

Int J Intell Syst

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The conflict problem in D-S evidence theory has attracted the attention of many scholars. Conflict coefficients are proposed to describe conflicts between bodies of evidence. The association coefficient as the opposite of the conflict coefficient is also used to measure the conflict. The larger the association coefficient, the smaller the conflict degree, and the higher the similarity between the evidence bodies, and vice versa.In this paper, the degree of association is defined by Deng Entropy, and a new association coefficient is proposed based on the basic inequality. The nature of the new association coefficient and conflict coefficients is explored using examples. Finally, the association coefficient combined with the D-S combination rule is applied to the target recognition system, and accurate results are obtained.association coefficient, conflict coefficients, conflict problem, Deng entropy, D-S evidence theory, target recognition system | INTRODUCTIONThe D-S evidence theory was first proposed by Dempster 1 in 1967 and later developed by his student Shafer 2 in 1976 as an imprecise reasoning theory, which is widely promoted. [3][4][5][6] The theory was first applied to expert systems, 7-9 and it was gradually applied in the fields of information fusion, 10-12 intelligence analysis, 9,13-16 evidential reasoning, [17][18][19] and multiattribute decision analysis. [20][21][22][23][24] As an indeterminate reasoning method which satisfies the conditions weaker than Bayesian probability theory; it has the ability to directly express "uncertainty" 25 and "don't know." 26 Therefore, the D-S evidence theory is flexible and convenient for describing uncertainties. However, D-S evidence theory has produced counterintuitive results in the fusion of a highly conflicting example proposed by Zadeh. 27 Therefore, the issue of conflict between bodies of evidence has attracted more and more researchers so far. [28][29][30][31][32] Domestic and foreign scholars have proposed a large number of improved methods, which can be divided into two major categories: (a) modification of the combination rules of the classical D-S evidence theory to achieve the redistribution of conflicts in the case of evidence conflicts. [33][34][35][36] Such measures alleviate the conflict between the bodies of evidence to a certain extent, but at the same time, it is difficult for the new rules to maintain the original properties of the D-S combination rules. (b) Keep the classic combination rules unchanged, and preprocess conflict data before combination. [37][38][39][40][41][42] Haenni 43 believes that the modification of the data model is in engineering, mathematics and philosophically more reasonable. However, regardless of the type of method used to deal with conflicts between evidence, the conflict coefficient is an extremely important parameter. Therefore, the most critical step before choosing the right combination of evidence is the measure of evidence conflict.To measure the conflict between evidence bodies, many researchers have proposed...

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Section: Preliminariesmentioning

confidence: 99%

An association coefficient of a belief function and its application in a target recognition system

Pan

Deng

2019

Int J Intell Syst

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“…Handling uncertainty is an open issue. 34,35 Many methods, such as rough sets, 36 Pythagorean fuzzy sets, 37 Z-numbers, 38,39 D-numbers, [40][41][42] evidential reasoning, [43][44][45] and others, [46][47][48][49] are proposed. Among these tools, Dempster-Shafer evidence theory is an efficient theory to deal with uncertainty.…”

Section: Dempster-shafer Evidence Theorymentioning

confidence: 99%

A new matrix game with payoffs of generalized Dempster‐Shafer structures

Zhou

Xiao

2019

Int J Intell Syst

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How to deal with matrix game under uncertainty is an open issue. Compared with the Dempster‐Shafer structure, the insignificant deviation caused by the subjectivity of the expert is effectively eliminated generalized Dempster‐Shafer structures. In this paper, a new matrix game with payoffs of generalized Dempster‐Shafer structures is presented. Generalized Dempster‐Shafer structures presents probability nonspecificity and inaccuracy as interval values. Then payoff is determined by linear programming. A zero‐sum matrix game is illustrated the efficiency of the proposed method.

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“…To improve the performance of blades, it is necessary to analyze the coupling mechanism between shockwave and boundary layer . Many valuable studies have been proposed to perform this analysis by means of numerical simulations combining with physics of failure modeling . Among them, Wang et al utilized a reliability index strategy and proposed an uncertainty‐based optimization model for the structure design problem with bounded uncertain information.…”

Section: Introductionmentioning

confidence: 99%

“…9 Many valuable studies have been proposed to perform Nomenclature: X R , continuous random variable; M XR ξ ð Þ, the moment generating function of X R ; K XR ξ ð Þ, the cumulant generating function of X R ; f XR x R ð Þ, the probability density function of X R ; e ξ, the saddlepoint; ϕ(•), the standard normal probability density function of X R ; Φ(•), the standard normal cumulant generating function of X R ; X, the vector of local design variables; X S , the vector of shared design variables; Y ji , the vector of coupling variables which are the output of discipline j; Y ij , the vector of coupling variables which are the output of discipline i; J, the compatibility constraint; Pr(•), the reliability constraints this analysis by means of numerical simulations combining with physics of failure modeling. [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25] Among them, Wang et al 10 utilized a reliability index strategy and proposed an uncertainty-based optimization model for the structure design problem with bounded uncertain information. Correia et al 11 proposed a generalization probabilistic fatigue model which can include multiaxial loading conditions and mean-stress effects.…”

Section: Introductionmentioning

confidence: 99%

Structural reliability analysis and uncertainties‐based collaborative design and optimization of turbine blades using surrogate model

Meng

Yang

Zhang³

et al. 2018

Fatigue Fract Eng Mat Struct

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137

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In power and energy systems, both the aerodynamic performance and the structure reliability of turbine equipment are affected by utilized blades. In general, the design process of blade is high dimensional and nonlinear. Different coupled disciplines are also involved during this process. Moreover, unavoidable uncertainties are transported and accumulated between these coupled disciplines, which may cause turbine equipment to be unsafe. In this study, a saddlepoint approximation reliability analysis method is introduced and combined with collaborative optimization method to address the above challenge. During the above reliability analysis and design optimization process, surrogate models are utilized to alleviate the computational burden for uncertainties‐based multidisciplinary design and optimization problems. Smooth response surfaces of the performance of turbine blades are constructed instead of expensively time‐consuming simulations. A turbine blade design problem is solved here to validate the effectiveness and show the utilization of the given approach.

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A modeling and analysis strategy of constellation availability using on-orbit and ground added launch backup and its application in the reliability design for a remote sensing satellite

Cited by 15 publications

References 16 publications

An association coefficient of a belief function and its application in a target recognition system

An association coefficient of a belief function and its application in a target recognition system

A new matrix game with payoffs of generalized Dempster‐Shafer structures

Structural reliability analysis and uncertainties‐based collaborative design and optimization of turbine blades using surrogate model

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