• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1651-1664
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• 2013

Precise analysis on deterioration processes of road pavements is not so simple matter due to severe uncertainty originated from a lot of explanatory variables engaged in. For those reasons, most analytical models for pavement deterioration prediction have often preferred to probabilistic approaches than deterministic models. However, the general probabilistic approaches that treat overall characteristics of population or entire sample would not be suitable for providing detail or localized information on their changing process. Considering the aspects, this paper aimed to suggest a stochastic disaggregation method to analyze the localized deterioration speeds and its variances changed by time and condition states. In addition, life expectancies and their uncertainty were estimated by probabilistic algorithm using the disaggregated stochastic process. For an empirical study, pavement inspection data (crack) accumulated from 2003 to 2010 from Korean national highway network was applied. This study can contribute to securing reliability of life cycle cost analysis, which is one of the primary analyses in road asset management, with much advanced deterioration forecasting functions. In addition, it would be meaningful trials as fundamental research for preventive maintenance strategy that demands essential understanding on changing process of the deterioration speed of pavement.

• Korean Journal of Construction Engineering and Management
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• v.17 no.2
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• pp.70-79
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• 2016

The current remodeling cost estimation process is not only dependent on the historical data of new building construction, but it also has a poor linkage with risk-based estimation approach. As such, there is a high risk of falling short of initial budget. To overcome this, a risk-based estimation approach is necessary by providing a probabilistic estimation in consideration of the potential risk factors in conducting the remodeling projects. In addition, the decision-making process should be linked with the risk-based estimation results in stead of intuitive and/or experience-based estimation. This study provides a probabilistic estimation process for residential remodeling projects by developing a detailed methodology in which a step-by-step approach can be achieved. The new proposed estimation approach can help in decision-making for remodeling projects in terms of whether to proceed or not, by effectively reflecting the potential risk factors in the early stage of the project. In addition, the study can enhance the reliability of the estimation results by developing a sustainable estimation process model where a risk-based evaluation can be accomplished by setting up the cost-risk relationship database structure.

• Journal of the Ergonomics Society of Korea
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• v.5 no.2
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• pp.11-15
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• 1986

In this paper, we consider the validity of a human probabilistic learning model applied to the perdiction of errors associated with the absolute identification of tones. It is shown that the probabilistic learning model describes the human error process adequately. The model parameters are estimated by two methods which are the method of maximum likelihood, and the method of mement. The MLE version of the model has the better predictive power but the ME version is more readily obtainable and may be more practical.

• 전기의세계
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• v.22 no.2
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• pp.28-32
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• 1973

System modeling is applied in developing a probabilistic linear estimator for the load of an electric power system for the purpose of short term load forecasting. The model assumer that the load in given by the suns of a periodic discrete time serier with a period of 24 hour and a residual term such that the output of a discrete time dynamical linear system driven by a white random process and a deterministic input. And also we have established the main forecasting algorithms, which are essemtally the Kalman filter-predictor equations.

• Journal of Information Management
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• v.21 no.1
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• pp.34-52
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• 1990

The probabilistic reasoning method using Bayesian theory is studied to use uncertain or incomplete knowledge in ways that take the uncertainty into account. This method presented for knowledge acquisition process of expert system to evaluate certainty degree of input knowledge.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2047-2052
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• 2023

Risk-informed approach has been widely applied in the safety design, regulation, and operation of nuclear reactors. It has been commonly accepted that risk-informed design optimization should be used in the innovative reactor designs to make nuclear system highly safe and reliable. In spite of the risk-informed approach has been used in some advanced nuclear reactors designs, such as Westinghouse IRIS, Gen-IV sodium fast reactors and lead-based fast reactors, the process of risk-informed design of nuclear reactors is hardly to carry out when passive system reliability should be integrated in the framework. A practical method for new passive safety reactors based on probabilistic safety assessment (PSA) and passive system reliability analyze linking is proposed in this paper. New three-dimension frequency-consequence curve based on risk concept with three variables is used in this method. The proposed method has been applied to the determination optimization of design options selection in a 10 MWth lead-based research reactor(LR) to obtain one optimized system design in conceptual design stage, using the integrated reliability and probabilistic safety assessment program RiskA, and the computation resources and time consumption in this process was demonstrated reasonable and acceptable.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.6
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• pp.551-561
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• 1991

The probabilistic generation simulation plays a key role in power system expansion and operational planning especially for the calculation of expected energy, loss of load probaility and unserved energy expected. However, it is crucial to develop a probabilistic generation simulation algorithm which gives sufficiently precise results within a reasonable computation time. In a previous paper, we have proposed an efficent method using Fast Hartley Transform in convolution process for considering the thermal and nuclear units. In this paper, a method considering the scheduling of pumped-storage plants and hydro plants with energy constraint is proposed. The method also adopts FHT techniques. We improve the model to include multi-state and multi-block generation. The method has been applied for a real size model system.

• Journal of Ocean Engineering and Technology
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• v.20 no.5 s.72
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• pp.70-76
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• 2006

A Probabilistic neural network (PNN) technique for predicting the stability number for the armor blocks of breakwaters is presented. A PNN is prepared using the experimental data of van der Meer and is then compared with the empirical formula and previous artificial neural network (ANN) model. This comparison shows that a PNN can effectively predict the stability numbers in spite of data complexity, incompleteness, and incoherence, and can be an effective tool for the designers of rubble mound breakwaters to support their decision process and to improve design efficiency.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.61-63
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• 2005

Retreiving indoor scene reference image from database using visual information is important issue in Robot Navigation. Scene matching problem in navigation robot is not easy because input image that is taken in navigation process is affinly distorted. We represent probabilistic framework for the feature matching between features in input image and features in database reference images to guarantee robust scene matching efficiency. By reconstructing probabilistic scene matching framework we get a higher precision than the existing feaure-feature matching scheme. To construct probabilistic framework we represent each image as Gaussian Mixture Model using Expectation Maximization algorithm using SIFT(Scale Invariant Feature Transform).

• Journal of the Korean Society for Precision Engineering
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• v.19 no.9
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• pp.90-97
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• 2002

Ceramics are being increasingly used in industry due to their outstanding physical and chemical properties. But these materials are difficult to machine by traditional machining processes, because they are hard and brittle. Recently, as one of various alternative processes, laser-beam machining is widely used in the cutting of ceramics. Although the use of lasers presents a number of advantages over other methods, one of the problems associated with this process is the uncertain formation of cracks that result from the thermal stresses. This paper presents a Bayesian probabilistic modeling of crack formation over thin alumina plates during laser cutting.