• 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.

• Industrial Engineering and Management Systems
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• v.12 no.1
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• pp.41-45
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• 2013

Age replacement policy is a commonly policy in maintenance management of spare part. It means that a spare part is always replaced at failure or fixed time after its installation, whichever occurs first. An optimal age replacement policy of spare parts concerns with finding the optimal replacement time determined by minimizing the expected cost per unit time. The age of the part was generally assumed to be a random variable in the past literatures, but in many situations, there are few or even no observed data to estimate the probability distribution of part's lifetime. In order to solve this phenomenon, a new uncertain age replacement policy has been proposed recently, in which the age of the part was assumed to be an uncertain variable. This paper discusses the optimal age replacement policies by dealing with the parts' lifetimes as different distributed uncertain variables. Several results on the optimal age replacement time are provided when the lifetimes are described by the uncertain linear, zigzag and lognormal distributions.

• Geomechanics and Engineering
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• v.22 no.4
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• pp.339-348
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• 2020

The uncertain geotechnical properties of frozen soil are important evidence for the design, operation and maintenance of the frozen ground. The complex geological, environmental and physical effects can lead to the spatial variations of the frozen soil, and the uncertain mechanical properties are the key factors for the uncertain analysis of frozen soil engineering. In this study, the elastic modulus, strength and Poisson ratio of warm frozen soil were measured, and the statistical characteristics under different temperature conditions are obtained. The autocorrelation distance (ACD) and autocorrelation function (ACF) of uncertain mechanical properties are estimated by random field (RF) method. The results show that the mean elastic modulus and mean strength decrease with the increase of temperature while the mean Poisson ratio increases with the increase of temperature. The average values of the ACD for the elastic modulus, strength and Poisson ratio are 0.64m, 0.53m and 0.48m, respectively. The standard deviation of the ACD for the elastic modulus, strength and Poisson ratio are 0.03m, 0.07m and 0.03m, respectively. The ACFs of elastic modulus, strength and Poisson ratio decrease with the increase of ratio of local average distance and scale of fluctuation. The ACF of uncertain mechanical properties is different when the temperature is different. This study can improve our understanding of the spatial autocorrelation variations of uncertain geotechnical properties and provide a basis and reference for the uncertain settlement analysis of frozen soil foundation.

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1229-1238
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• 2002

In this paper, a method to obtain the sensitivity of eigenvalues and the random responses of the structure with uncertain parameters is proposed. The concept of the proposed method is that the perturbed equation of each uncertain substructure is obtained using the finite element method, and the perturbed equation of the overall structure is obtained using the mode synthesis method. By this way, the reduced order perturbed equation of the uncertain system can be obtained. And the response of the uncertain system is obtained using probability method. As a numerical example, a simple piping system is considered as an example structure. The damping and spring constants of the support are considered as the uncertain parameters. Then the variations of the eigenvalues, the correlation function and the power spectral density function of the responses are calculated. As a result, the proposed method is considered to be useful technique to analyze the sensitivities of eigenvalues and random response against random excitation in terms of the accuracy and the calculation time.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.63-76
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• 2016

Multiperiod portfolio selection problem attracts more and more attentions because it is in accordance with the practical investment decision-making problem. However, the existing literature on this field is almost undertaken by regarding security returns as random variables in the framework of probability theory. Different from these works, we assume that security returns are uncertain variables which may be given by the experts, and take absolute deviation as a risk measure in the framework of uncertainty theory. In this paper, a new multiperiod mean absolute deviation uncertain portfolio selection models is presented by taking transaction costs, borrowing constraints and threshold constraints into account, which an optimal investment policy can be generated to help investors not only achieve an optimal return, but also have a good risk control. Threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Based on uncertain theories, the model is converted to a dynamic optimization problem. Because of the transaction costs, the model is a dynamic optimization problem with path dependence. To solve the new model in general cases, the forward dynamic programming method is presented. In addition, a numerical example is also presented to illustrate the modeling idea and the effectiveness of the designed algorithm.

• Communications of the Korean Mathematical Society
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• v.35 no.3
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• pp.907-916
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• 2020

In this paper, we introduce the notion of p-distance in a complex uncertain sequence space. By using the concepts of p-distance, we give some theorems of convergence. Also, in a complex uncertain sequence space, we develope some properties on convergence in measure.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.55-59
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• 1991

This paper presents a method for designing a full state feedback linear static control law. This will stabilize a given linear uncertain system and also guarantee the performance of the system. The uncertain systems are described by state equation which contains uncertain parameters in system and input distribution matrices. The method is based on the guaranteed cost control of Chang and Peng(1972). The controller gain can be obtained by the solution of a algebraic Riccati equation in which the input weighting matrices depend on the uncertainty bounds. The algebraic Riecati equation in this paper is same as that of weighted LQ regulator problem.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.2
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• pp.87-93
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• 2014

Cadastral parcel objects as polygons are fundamental dataset which represent land administration and management of the real world. Thus it is necessary to assure topological seamlessness of cadastral datasets which means no overlaps or gaps between adjacent parcels. However, the problem of overlaps or gaps are frequently found due to non-coinciding edges between adjacent parcels. These erroneous edges are called uncertain edges, and polygons containing at least one uncertain edge are called uncertain polygons. In this paper, we proposed a new algorithm to efficiently search parcels of uncertain polygons between two adjacent cadastral datasets. The algorithm first selects points and polylines around adjacent datasets. Then the Constrained Delaunay Triangulation (CDT) is applied to extract triangles. These triangles are tagged by the number of the original cadastral datasets which intersected with the triangles. If the tagging value is zero, the area of triangles mean gaps, meanwhile, the value is two, the area means overlaps. Merging these triangles with the same tagging values according to adjacency analysis, uncertain edges and uncertain polygons could be found. We have performed experimental application of this automated derivation of partitioned boundary from a real land-cadastral dataset.

• 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 Industrial Technology
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• v.10
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• pp.3-8
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• 1990

This paper presents a linear state feedback control approach to the stabilization of discrete-time uncertain systems with bounded uncertain parameters. The approach is based on the LQ(linear quadratic) regulator theory and Lyapunov's stability analysis. Asymptotically stable behavior is guaranteed in the presence of parameter uncertainties, and the upper bound of the performance index is determined.