• Industrial Engineering and Management Systems
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• v.15 no.2
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• pp.143-147
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• 2016

Uncertainty appears not only in real quantities but also in complex quantities. Complex uncertain process is essentially a sequence of complex uncertain variables indexed by time. In order to describe complex uncertain process, a formal definition of complex uncertain distribution is given in this paper, as well as the concepts of independence and variance. In addition, some properties of complex uncertain integral are presented.

• Journal of Information Technology Applications and Management
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• v.14 no.4
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• pp.139-158
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• 2007

Information sharing is key to effective supply chain management. In reality, however, it is impossible to get perfect information. Accordingly, only uncertain information can be accessed in business environment, and thus it is important to deal with the uncertainties of information in managing supply chains. This study adopts meteorological forecast as a typical uncertain information. The meteorological events may affect the demands for various weather-sensitive goods, such as beer, ices, clothes, electricity etc. In this study, a beer distribution game is modified by introducing meterological forecast information provided in a probabilistic format. The behavior patterns of the modified beer supply chains are investigated. for two conditions using the weather forecast with or without an information sharing. A value score is introduced to generalize the well-known performance measures employed in the study of supply chains, i.e.. inventory, backlog, and deviation of orders. The simulation result showed that meterological forecast information used in an information sharing environment was more effective than without information sharing, which emphasizes the synergy of uncertain information added to the information sharing environment.

• Industrial Engineering and Management Systems
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• v.12 no.1
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• pp.2-8
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• 2013

Uncertainty theory is a branch of mathematics based on normolity, duality, subadditivity and product axioms. Uncertain process is a sequence of uncertain variables indexed by time. Canonical Liu process is an uncertain process with stationary and independent increments. And the increments follow normal uncertainty distributions. Uncertain differential equation is a type of differential equation driven by the canonical Liu process. Stability analysis on uncertain differential equation is to investigate the qualitative properties, which is significant both in theory and application for uncertain differential equations. This paper aims to study stability properties of linear uncertain differential equations. First, the stability concepts are introduced. And then, several sufficient and necessary conditions of stability for linear uncertain differential equations are proposed. Besides, some examples are discussed.

• Journal of KIISE:Software and Applications
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• v.37 no.2
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• pp.148-154
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• 2010

In the study of the formal semantics of uncertain databases, we typically take an algebraic approach by mapping an uncertain database to possible worlds which are a set of relational databases. In this paper, we present a new semantics for uncertain databases which takes a logical approach by translating uncertain databases into logical theories. A characteristic feature of our semantics is that it uses linear logic, instead of propositional logic, as its logical foundation. Linear logic is suitable for a logical interpretation of uncertain information because unlike propositional logic, it treats logical formulae not as persistent facts but as consumable resources. As the main result, we show that our semantics is faithful to the operational account of uncertain databases in the algebraic approach.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.571-574
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• 2005

This paper gives some sufficient conditions for a given polyhedral set which is represented as a set of linear inequalities to be positive D-invariant for uncertain linear discrete-time systems in the case such that the systems matrices depend linearly on uncertain parameters whose ranges are given intervals. Further, the results will be applied to uncertain linear continuous systems in the sense of the above by using Euler approximation.

• Journal of the Korean Data and Information Science Society
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• v.6 no.2
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• pp.17-27
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• 1995

We propose a framework for representing and processing uncertain knowledge on the basis of constraint satisfaction. A system of equations and/or inequalities can be considered as a set of constraints that should be solved, and each constraint in the set is transformed into a corresponding logical formula which can be solved through a constraint solving program. Most of rule-based systems, for instance, use a simple probabilistic theory in order to maintain uncertain knowledge, therefore uncertain knowledge can be represented and processed in the constraint satisfaction program quite efficiently.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.117-119
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• 1997

We consider the control design for nonlinear uncertain systems. The uncertainty is mismatched and possibly fast time-varying. Within the suitable range of the uncertainty the control is valid. No statistical information on uncertainty is imposed. Only the possible bound of the uncertain parameter is known and the control design is based on Lyapunov approach.

• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.1-7
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• 1997

The inference process for medical expert system is mostly formed by diagnostic knowledge on the if-then rule base. Oriental medicine diagnostic knowledge, however, may involve uncertain knowledge caused by ambiguous concept. In this paper, we analyze an oriental medicine diagnostic process by a rule-based inference system, and propose a method for representing and processing uncertain oriental medicine diagnostic knowledge using CLP( R ) which is a kind of constraint satisfaction program.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.6
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• pp.1542-1550
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• 1994

For a class of singularly perturbed uncertain system, an output feedback control law is designed. The controller structure is designed based on the uncertain reduced-order system, and the controller parameters are determined by information on the reduced-order and full-order systems. It has been shown that the reduces-order system with the designed controller possesses a stability property(specifically, a global uniform attractivity). Furthermore, the stability property of this control scheme is robust with respect to singular perturbation ; i.e., the full-order system, subject to the same controller, possesses the global uniform attractivity, provided the singular perturbation parameter $\mu<\mu^{*}$, where a threshold value $\mu^{*}$ can be computed from the information available on the full-order system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2986-2999
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• 2019

The uncertainties of the uncertain graph make the traditional definition and algorithms on mining dense graph for certain graph not applicable. The subgraph obtained by maximizing expected density from an uncertain graph always has many low edge-probability data, which makes it low reliable and low expected edge density. Based on the concept of ${\beta}$-subgraph, to overcome the low reliability of the densest subgraph, the concept of optimal ${\beta}$-subgraph is proposed. An efficient greedy algorithm is also developed to find the optimal ${\beta}$-subgraph. Simulation experiments of multiple sets of datasets show that the average edge-possibility of optimal ${\beta}$-subgraph is improved by nearly 40%, and the expected edge density reaches 0.9 on average. The parameter ${\beta}$ is scalable and applicable to multiple scenarios.