• Journal of Korean Institute of Industrial Engineers
• /
• v.15 no.2
• /
• pp.109-116
• /
• 1989

In many cases, production-inventory systems involves significant demand variations. Actual demand is probabilistic and the production capacity is also limited. Finding the proper production lot sizes to this problem usually requires heavy computational procedures. Therefore a heuristic approach were under various assumptions is highly recommended. In this paper, an approach with consideration of probabilistic demand and limited production capacity is proposed.

• East Asian mathematical journal
• /
• v.36 no.1
• /
• pp.55-60
• /
• 2020

We study a probabilistic approach for valuing an exchange option with default risk. The structural model of Klein [6] is used for modeling default risk. Under the structural model, we derive the closed-form pricing formula of the exchange option with default risk. Specifically, we provide the pricing formula of the option with the bivariate normal cumulative function via a change of measure technique and a multidimensional Girsanov's theorem.

• Journal of the Chungcheong Mathematical Society
• /
• v.22 no.4
• /
• pp.623-633
• /
• 2009

The classical Mazur-Ulam theorem states that every surjective isometry between real normed spaces is affine. In this paper, we study 2-isometries in probabilistic 2-normed spaces.

• Journal of applied mathematics & informatics
• /
• v.19 no.1_2
• /
• pp.363-370
• /
• 2005

In this paper, we obtain a new fixed point theorem in complete probabilistic ${\Delta}$-inner product space. As an example of applications, we utilize the results of this paper to study the existence and uniqueness of solutions for linear Valterra integral equation.

• Computers and Concrete
• /
• v.3 no.2_3
• /
• pp.123-144
• /
• 2006

Reinforced concrete corbels are structural elements widely used in practical engineering. The complex response of these elements is described in design codes in a simplified manner. These formulations are not sufficient to show the real behavior, which, however, is an essential prerequisite for the manufacturing of numerous elements. Therefore, a deterministic and probabilistic study has been performed, which is described in this contribution. Real complex structures have been modeled by means of the finite element method supported primarily by experimental works. The main objective of this study was the detection of uncertainties effects and safety margins not captured by traditional codes. This aim could be fulfilled by statistical considerations applied to the investigated structures. The probabilistic study is based on advanced Monte Carlo simulation techniques and sophisticated nonlinear finite element formulations.

• Journal of The Korean Association For Science Education
• /
• v.25 no.7
• /
• pp.787-793
• /
• 2005

The purposes of this study were to investigate the development of probabilistic thinking in relation to the cognitive level of elementary school students and to analyze the effects of probability activities in Thinking Science(TS) program on the development of probabilistic thinking. 152 6th grade elementary school students compiled the sample group which was divided into an experimental group and a control group. Probability activities in TS program were used with the experimental group, while the normal curriculum was conducted with the control group. Both the experimental and control group were assessed with Science Reasoning Task II and a probabilistic thinking test before execution of this investigation and were post-tested with probabilistic thinking test after the project period was complete. Results of this study showed that the students in the concrete operational stage and transitional stage used subjective strategy together with quantitative strategy in probability problem-solving, and students in the early formal operational stage used quantitative strategy in probability problem-solving. It was also found that the higher the cognitive level of students, the higher the probabilistic thinking level. The probability activities of the TS program influenced the development of probabilistic thinking of elementary school students. Assessing the development of probabilistic thinking on the basis of the cognitive level found that the level of effectiveness was significantly higher for students in the early concrete operational stage and transitional stage than students in any other stage.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.8 no.2
• /
• pp.159-167
• /
• 2004

The compressive strength of concrete is a criterion to produce concrete. However, the tests on the compressive strength are complicated and time-consuming. More importantly, it is too late to make improvement even if the test result does not satisfy the required strength, since the test is usually performed at the 28th day after the placement of concrete at the construction site. Therefore, strength prediction before the placement of concrete is highly desirable. This study presents the probabilistic technique for predicting the compressive strength of concrete on the basis of concrete mix proportions. The estimation of the strength is based on the probabilistic neural network which is an effective tool for pattern classification problem and gives a probabilistic result, not a deterministic value. In this study, verifications for the applicability of the probabilistic neural networks were performed using the test results of concrete compressive strength. The estimated strengths are also compared with the results of the actual compression tests. It has been found that the present methods are very efficient and reasonable in predicting the compressive strength of concrete probabilistically.

• Journal of Korea Water Resources Association
• /
• v.50 no.8
• /
• pp.563-577
• /
• 2017

As the uncertainty of precipitation increases due to climate change, seasonal forecasting and the use of weather forecasts become essential for efficient water resources management. In this study, the categorical probabilistic long-term forecasts implemented by KMA (Korea Meteorological Administration) since June 2014 was evaluated using assessment indicators of Hit Rate, Reliability Diagram, and Relative Operating Curve (ROC) and a technique for obtaining quantitative precipitation estimates based on probabilistic forecasts was proposed. The probabilistic long-term forecasts showed its maximum predictability of 48% and the quantified precipitation estimates were closely matched with actual observations; maximum correlation coefficient (R) in predictability evaluation for 100% accurate and actual weather forecasts were 0.98 and 0.71, respectively. A precipitation quantification approach utilizing probabilistic forecasts proposed in this study is expected to enable water management considering the uncertainty of precipitation. This method is also expected to be a useful tool for supporting decision-making in the long-term planning for water resources management and reservoir operations.

• Proceedings of the KOSOMBE Conference
• /
• v.1991 no.05
• /
• pp.65-70
• /
• 1991

A hybrid model which uses a probabilistic model and a MLP(multi layer perceptron) model for pattern recognition of EMG(electromyogram) signals is proposed in this paper. MLP model has problems which do not guarantee global minima of error due to learning method and have different approximation grade to bayesian probabilities due to different amounts and quality of training data, the number of hidden layers and hidden nodes, etc. Especially in the case of new test data which exclude design samples, the latter problem produces quite different results. The error probability of probabilistic model is closely related to the estimation error of the parameters used in the model and fidelity of assumtion. Generally, it is impossible to introduce the bayesian classifier to the probabilistic model of EMG signals because of unknown priori probabilities and is estimated by MLE(maximum likelihood estimate). In this paper we propose the method which get the MAP(maximum a posteriori probability) in the probabilistic model by estimating the priori probability distribution which minimize the error probability using the MLP. This method minimize the error probability of the probabilistic model as long as the realization of the MLP is optimal and approximate the minimum of error probability of each class of both models selectively. Alocating the reference coordinate of EMG signal to the outside of the body make it easy to suit to the applications which it is difficult to define and seperate using internal body coordinate. Simulation results show the benefit of the proposed model compared to use the MLP and the probabilistic model seperately.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.39 no.1
• /
• pp.63-69
• /
• 2015

The primary aim of this paper is to evaluate the probabilistic fatigue crack propagation models using the residual of a random variable and to present the probabilistic model fit for the probabilistic fatigue crack growth behavior in Mg-Al-Zn alloys under maximum load conditions. The models used in this study were prepared by applying a random variable to empirical fatigue crack propagation models such as the Paris-Erdogan model, Walker model, Forman model, and modified Forman model. It was verified that the good models for describing the stochastic variation of the fatigue crack propagation behavior in Mg-Al-Zn alloys under maximum load conditions were the 'probabilistic Paris-Erdogan model' and 'probabilistic Walker model'. The influence of the maximum load conditions on the stochastic variation of fatigue crack growth is also considered.