• Industrial Engineering and Management Systems
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• 제11권2호
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• pp.176-182
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• 2012

This paper presents a new approach to risk comparison in uncertain environment. Based on the uncertainty theory, some uncertain risk measures and risk comparison rules are proposed. Afterward the bridges are built between uncertain risk measures and risk comparison rules. Finally, several comparable examples are given.

• 대한수학회논문집
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• 제35권3호
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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.

• Industrial Engineering and Management Systems
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• 제15권1호
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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.

• 대한수학회논문집
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• 제36권1호
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• pp.121-134
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• 2021

In this paper we introduce the notion of paranormed p-absolutely convergent and paranormed Cesro summable sequences of complex uncertain variables with respect to measure, mean, distribution etc. defined by on Orlicz function. We have established some relationships among these notions as well as with other classes of complex uncertain variables.

• Journal of applied mathematics & informatics
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• 제40권1_2호
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• pp.191-204
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• 2022

This paper introduces the statistical convergence concepts of double sequences of complex uncertain variables: statistical convergence almost surely(a.s.), statistical convergence in measure, statistical convergence in mean, statistical convergence in distribution and statistical convergence uniformly almost surely(u.a.s.).

• Industrial Engineering and Management Systems
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• 제11권2호
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• pp.183-187
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• 2012

In this paper, we study the fixed charge transportation problem with uncertain variables. The fixed charge transportation problem has two kinds of costs: direct cost and fixed charge. The direct cost is the cost associated with each source-destination pair, and the fixed charge occurs when the transportation activity takes place in the corresponding source-destination pair. The uncertain fixed charge transportation problem is modeled on the basis of uncertainty theory. According to inverse uncertainty distribution, the model can be transformed into a deterministic form. Finally, in order to solve the uncertain fixed charge transportation problem, a numerical example is given to show the application of the model and algorithm.

• Nuclear Engineering and Technology
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• 제50권8호
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• pp.1412-1420
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• 2018

An experiment was performed using the large-scale test facility (LSTF), which simulated a 1% vessel upper head small-break loss-of-coolant accident with an accident management (AM) measure under an assumption of total-failure of high-pressure injection (HPI) system in a pressurized water reactor (PWR). In the LSTF test, liquid level in the upper head affected break flow rate. Coolant was manually injected from the HPI system into cold legs as the AM measure when the maximum core exit temperature reached 623 K. The cladding surface temperature largely increased due to late and slow response of the core exit thermocouples. The AM measure was confirmed to be effective for the core cooling. The RELAP5/MOD3.3 code indicated insufficient prediction of primary coolant distribution. The author conducted uncertainty analysis for the LSTF test employing created phenomena identification and ranking table for each component. The author clarified that peak cladding temperature was largely dependent on the combination of multiple uncertain parameters within the defined uncertain ranges.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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• pp.9-12
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• 2002

Representation and quantification of fuzziness are required for the uncertain system modelling and controller design. Conventional results show that entropy of fuzzy sets represent the fuzziness of fuzzy sets. In this literature, the relations of fuzzy enropy, distance measure and similarity measure are discussed, and distance measure is proposed. With the help of relations of fuzzy enropy, distance measure and similarity measure, fuzzy entropy is represented by the newly proposed distance measure. With simple fuzzy set, example is illustrated.

• Journal of applied mathematics & informatics
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• 제31권1_2호
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• pp.99-110
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• 2013

In this article, sensitivity analysis of atmospheric dispersion model RIMPUFF is considered. Uncertain parameters are taken to be triangular fuzzy numbers, and sensitivity analysis is carried out by using the Hartley-like measure. Codes for evaluating membership function using the Vertex method and the Hartley-like measure are prepared using Matlab.

• Journal of KIEE
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• 제11권1호
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• pp.8-13
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• 2001

In this brief, the design method of robust non-fragile decentralized controllers for uncertain large-scale interconnected systems is proposed. Based on Lyapunov second method, a sufficient condition for asymtotic stability is derived in terms of a linear matrix inequality (LMI), and the measure of non-fragility in controller is presented. The solutions of the LMI can be easily obtained using efficient convex optimization techniques. A numerical example is given to illustrate the proposed method.