• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.233-238
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• 2016

In this paper, we propose the algorithms of processing the uncertainty data using data fusion for the next generation intrusion detection. In the next generation intrusion detection, a lot of data are collected by many of network sensors to discover knowledge from generating information in cyber space. It is necessary the data fusion process to extract knowledge from collected sensors data. In this paper, we have proposed method to represent the uncertainty data, by classifying where is a confidence interval in interval of uncertainty data through feature analysis of different data using inference method with Dempster-Shafer Evidence Theory. In this paper, we have implemented a detection experiment that is classified by the confidence interval using IRIS plant Data Set for anomaly detection of uncertainty data. As a result, we found that it is possible to classify data by confidence interval.

• Nuclear Engineering and Technology
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• v.19 no.1
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• pp.10-21
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• 1987

Uncertainty analysis of the FLB accident is performed for KNU-1 using the response surface methodology and Monte Carlo simulation. The FLB analyses using the RELAP4/Mod6 were performed a number of times to generate the data base for the uncertainty analysis, along with the EM calculation for comparison purpose. Two kinds of input sets are utilized for response surface method to investigate and compare the effects of the uncertainty of input variables on the RCS peak pressure following a FLB. The first set is composed of six major plant operational parameters and the second set is composed of five major modelling parameters. It is found through the analysis of results that the uncertainties of modelling parameters have more influence on the RCS peak pressure than the uncertainties of plant operational parameters and that the extra margin of 9% of peak pressure is gained. And one of the assumptions of EM calculation, which is usually accepted as conservative is found to be erroneous, that is, the initial core inlet temperature is found to act negatively on the RCS pressure following a FLB.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.513-518
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• 1996

This report presents a demonstration of application of realistic evaluation methodology to a posturated cold leg large break LOCA in a Westinghouse three-loop pressurized water reactor with 17$\times$17 fuel. The new method of this analysis can be divided into three distinct step: 1) Best Estimate Code Validation and Uncertainty Quantification 2) Realistic LOCA Calculation 3) Limiting Value LOCA Calculation and Uncertainty Combination RELAP5/MOD3/K ［1］, which was improved from RELAP5/MOD3.1, and CONTEMPT4/MOD5 code were used as a best estimate thermal-hydraulic model for realistic LOCA calculation. The code uncertainties which will be determined in step 1) were quantified already in previous study ［2］, and thus the step 2) and 3) for plant application were presented in this paper. The application uncertainty parameters are divided into two categories, i.e. plant system parameters and fuel statistical parameters. Single parameter sensitivity calculations were performed to select system parameters which would be set at their limiting value in Limiting Value Approach (LVA) calculation. Single run of LVA calculation generated 27 PCT data according to the various combinations of fuel parameters and these data provided input to response surface generation. The probability distribution function was generated from Monte Carlo sampling of a response surface and the upper 95$^{th}$ percentile PCT was determined. Break spectrum analysis was also made to determine the critical break size. The results show that sufficient LOCA margin can be obtained for the demonstration NPP.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.429-434
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• 1996

K-REM［1］, which is under development as a realistic evaluation model of large break LOCA, is applied to the analysis of cold leg guillotine break of Ulchin 3&4. Fuel parameters on which statistical analysis of their effects on the peak cladding temperature (PCT) are made and system parameters on which the concept of limiting value approach (LVA) are applied, are determined from the single parameter sensitivity study. 3 parameters of fuel gap conductance, fuel thermal conductivity and power peaking factor are selected as fuel related ones and 4 parameters of axial power shape, reactor power, decay heat and the gas pressure of safety injection tank (SIT) are selected as plant system related ones. Response surface of PCT is generated from the plant calculation results and on which Monte Carlo sampling is made to get plant application uncertainty which is statistically combined with code uncertainty to produce the 95th percentile PCT. From the break spectrum analysis, blowdown PCT of 1350.23 K and reflood PCT of 1195.56 K are obtained for break discharge coefficients of 0.8 and 0.5, respectively.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.4
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• pp.13-22
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• 2007

The uncertainty in water quality model predictions is inevitably high due to natural stochasticity, model uncertainty, and parameter uncertainty. An integrated modeling system under uncertainty was described and demonstrated for use in watershed management and receiving-water quality prediction. A watershed model (HSPF), a receiving water quality model (WASP), and a wetland model (NPS-WET) were incorporated into an integrated modeling system (modified-BASINS) and applied to the Hwaseong Reservoir watershed. Reservoir water quality was predicted using the calibrated integrated modeling system, and the deterministic integrated modeling output was useful for estimating mean water quality given future watershed conditions and assessing the spatial distribution of pollutant loads. A Monte Carlo simulation was used to investigate the effect of various uncertainties on output prediction. Without pollution control measures in the watershed, the concentrations of total nitrogen (T-N) and total phosphorous (T-P) in the Hwaseong Reservoir, considering uncertainty, would be less than about 4.8 and 0.26 mg 4.8 and 0.26 mg $L^{-1}$, respectively, with 95% confidence. The effects of two watershed management practices, a wastewater treatment plant (WWTP) and a constructed wetland (WETLAND), were evaluated. The combined scenario (WWTP + WETLAND) was the most effective at improving reservoir water quality, bringing concentrations of T-N and T-P in the Hwaseong Reservoir to less than 3.54 and 0.15 mg ${L^{-1}$, 26.7 and 42.9% improvements, respectively, with 95% confidence. Overall, the Monte Carlo simulation in the integrated modeling system was practical for estimating uncertainty and reliable in water quality prediction. The approach described here may allow decisions to be made based on probability and level of risk, and its application is recommended.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.422-425
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• 1997

We consider the robust control problem for nonminimum phase(NMP) systems with parametric uncertainty which appear often in aircraft and missile control. First, a new method that makes such an uncertain NMP system to be factored as a interval minimum phase(MP) transfer function and a time delay term in the Pade approximation form has been presented. The controller to be proposed consists of a compensator $C_{Q}$(s) with Smith predictor in the internal model control(IMC) structure, so that it can have good robustness and performance against the structured uncertainty and the time delay behaviour due to NMP plant the $C_{Q}$(s) is designed on the MP model by using QFT. The stability and performance of overall system has been evaluated by the generalized Kharitonov theorem.rem.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.355-359
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• 1993

This paper deals with the problem of robust TDF(Two Degree of Freedom) H$_{\infty}$ control design for a linear system with parameter uncertainty in the state space model. The uncertain system considered here is with the time-invariant norm-bounded parameter uncertainty in the state matrix. A TDF H$_{\infty}$ control design is presented which robustly stabilizes the plant, guarantees the robust H$_{\infty}$ performance and improves the tracking performance for the closed-loop system in the face of parameter uncertainty. It is shwon that a suitable stabilizing control law can be constructed in terms of a positive definite solution to a certain parameter-dependent algebraic Riccati equation and a good tracking performance can be constructed in terms of suitable feedforward control law.aw.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.351-354
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• 1993

In this paper, reheat-fan engine is described as class of models constructed from nominal and uncertainty model for robust control. In this class of models, uncertainty model consists of structured and unstructured uncertainty, and each model is identified from nonlinear simulation using FFT and ML technique. Then, control requirements and augmented plant are specified. H$_{\infty}$ controller satisfying the control requirements is designed by using constant scaling matrix. Finally, efficacy of the H$_{\infty}$ controller is showed by computer simulation.n.

• Journal of Institute of Control, Robotics and Systems
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• v.1 no.2
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• pp.88-93
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• 1995

This paper presents a study using neural networks in the design of the tracking controller of robotic systems. Our strategy is to put to use the available knowledge about the robot manipulator, such as estimation models, in the contoller design via the computed torque method, and then to add the neural network to control the remaining uncertainty. The neural network used here learns to provide the inverse dynamics of the plant uncertainty, and acts as an inverse controller. In the simulation study, we verify that the proposed neural network controller is robust not only to structured uncertainties, but also to unstructured uncertainties such as friction models.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.272-272
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• 2000

since the controller is part or the overall closed-Loop system, it is necessary that the designed controller be able to tolerate some uncertainty in its coefficients. The adequate stability and performance margins are required for the designed nominal controllers. In the paper. we study the method to design the non-fragile fixed-structured controller for real parametric uncertain systems. When we impose the controller parameter perturbation, the structure of the controller must be given. Therefore, we assume that the controller has fixed-structure. The fixed-structure controller is practically necessary especially when the robust controller synthesis results in a high-order controller. In SISO systems, we propose the robust controller design method using the Mapping theorem. In the method, the plant uncertainty and controller Parameter are of the multilineal form in the stability and performance conditions. Then, the controller synthesis problem is easily recast to Linear Programming Problem.