• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.589-598
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• 2002

The color measuring/matching expert system is implemented with a new color measuring method that combines intelligent algorithms with image processing techniques. Color measuring part of the proposed system preprocesses the scanned original color input images to eliminate their distorted components by means of the image histogram technique of image pixels, and then extracts RGB(Red, Green, Blue)data among color information from preprocessed color input images. If the extracted RGB color data does not exist on the matching recipe databases, we can measure the colors for the user who want to implement the model that can search the rules for the color mixing information, using the intelligent modeling techniques such as fuzzy inference system and adaptive neuro-fuzzy inference system. Color matching part can easily choose images close to the original color for the user by comparing information of preprocessed color real input images with data-based measuring recipe information of the expert, from the viewpoint of the delta Eformula used in practical process.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.12-14
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• 2005

In this paper, we propose a new architecture of Self-Organizing Fuzzy Polynomial Neural Networks(SOFPNN) by means of genetically optimized fuzzy polynomial neuron(FPN) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially genetic algorithms(GAs). The conventional SOFPNNs hinges on an extended Group Method of Data Handling(GMDH) and exploits a fixed fuzzy inference type in each FPN of the SOFPNN as well as considers a fixed number of input nodes located in each layer. The design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics (such as the number of input variables, the order of the polynomial of the consequent part of fuzzy rules, a collection of the specific subset of input variables, and the number of membership function) and addresses specific aspects of parametric optimization. Therefore, the proposed SOFPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional SOFPNNs. To evaluate the performance of the genetically optimized SOFPNN, the model is experimented with using two time series data(gas furnace and chaotic time series).

• Proceedings of the KIEE Conference
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• 2005.11b
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• pp.162-164
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• 2005

This paper presents an hour-ahead System Marginal Price (SMP) forecasting framework based on a neural network. Recently, the deregulation in power industries has impacted on the power system operational problems. The bidding strategy of market participants in energy market is highly dependent on the short-term price levels. Therefore, short-term SMP forecasting is a very important issue to market participants to maximize their profits. and to market operator who may wish to operate the electricity market in a stable sense. The proposed hybrid neural network is composed of tow parts. First part of this scheme is pattern classification to input data using Kohonen Self-Organizing Map (SOM) and the second part is SMP forecasting using back-propagation neural network that has three layers. This paper compares the forecasting results using classified input data and unclassified input data. The proposed technique is trained, validated and tested with historical date of Korea Power Exchange (KPX) in 2002.

• Tunnel and Underground Space
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• v.9 no.3
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• pp.221-229
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• 1999

Parameters of failure criteria, compressive strength and elastic modulus are most important for design and stability analysis of rock structure using numerical analysis. In this study, it suggests that the application of input data for numerical analysis by the literature study and the result of the 150 sets of triaxial compressive test. There was much different between parameters of failure criterion suggested by Hoek-Brown and parameters resulted from the analysis using 150 sets of triaxial compressive test. But the converting equations of compressive strength have had an interrelation with RMR. However, the converting of elastic of elastic modulus were different as chosen of equation, and the equation by Nicholson et at was more useful than others.

• Journal of Environmental Science International
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• v.16 no.5
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• pp.561-569
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• 2007

This study used SCS-CN method to estimate the real recharge of the study area which is one of the most reasonable techniques to estimate groundwater recharge when there is no available runoff data in a watershed. From the results of tile real recharge analysis for the study area using SCS-CN method, it was analyzed that the year 1994 when the drought was severe shotted the lowest recharge of 106.3mm with recharge rate of 12.4%, and the highest recharge of 285.6mm with recharge rate of 21.8% occurred in 1990. Yearly average recharge of 213.2mm was obtained, and tile average recharge rate was 16.9%/year. KOG-FLOW model which has powerful post process functions consists of setting environments for input parameters in Korean language, and help function is added to each input data. Detailed information for each parameter is displayed when the icon is placed on the input parameters, and geologic boundaries or initial head data for each layer can be set easily on work sheet. The relative errors (R. E.) for each model's observed values and calculated values are $0.156{\sim}0.432$ in case of KOG-FLOW, and $0.451{\sim}1.175$ in case of WINFLOW, therefore it is known that KOG-FLOW model developed in this study produced results compared to observed head values.

• Fire Science and Engineering
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• v.30 no.5
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• pp.18-25
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• 2016

National performance-based design methods and prescribed standards for various input data not defined as separated regulation, ASET and RSET fire and evacuation simulations on the data cited by different designers. This is also directly connected reliability problems for the evacuation simulation and performance-based fire. standardizing the various input to performance-based fire and evacuation simulations of a similar risk, regardless of the experience of designer or technical skills. The performance-based targets proper fire-fighting and emergency equipment installed reasonable initial investment cost to done ensure safety.

• International Journal of Control, Automation, and Systems
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• v.4 no.3
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• pp.293-301
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• 2006

A new discretization method for calculating a sampled-data representation of a nonlinear continuous-time system is proposed. The proposed method is based on the well-known Taylor series expansion and zero-order hold (ZOH) assumption. The mathematical structure of the new discretization method is analyzed. On the basis of this structure, a sampled-data representation of a nonlinear system with a time-delayed input is derived. This method is applied to obtain a sampled-data representation of a non-affine nonlinear system, with a constant input time delay. In particular, the effect of the time discretization method on key properties of nonlinear control systems, such as equilibrium properties and asymptotic stability, is examined. 'Hybrid' discretization schemes that result from a combination of the 'scaling and squaring' technique with the Taylor method are also proposed, especially under conditions of very low sampling rates. Practical issues associated with the selection of the method parameters to meet CPU time and accuracy requirements are examined as well. The performance of the proposed method is evaluated using a nonlinear system with a time-delayed non-affine input.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.7
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• pp.1546-1552
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• 2004

Electronic Ink is a stored data in the form of the handwritten text or the script without converting it into ASCII by handwritten recognition on the pen-based computers and Personal Digital Assistants(Pocket PC) for supporting natural and convenient data input. One of the most important issues is to search the electronic ink in order to use it. We proposed and implemented a script matching algorithm for the electronic ink. Proposed matching algorithm separated the input stroke into a set of primitive stroke using the curvature of the stroke curve. After determining the type of separated strokes, it produced a stroke feature vector. And then it calculated the distance between the stroke feature vector of input strokes and one of strokes in the database using the dynamic programming technique.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.384-388
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• 2000

One-port acoustic characteristics of an in-duct source can be measured by the multi-load method using an overdetermined set of open pipes with different lengths as applied loads. The input data. viz. load pressure and load impedance, are usually contaminated by measurement error in the actual measurements, which result in errors in the calculated source parameters. In this paper, the effects of the errors in the input data on the results have been studied numerically, varying the number of loads and their impedances in order to determine what combination of the loads will yield the best result. An error analysis is applied to each case of possible loads, which consist of open pipes. It is noted that, frequently, only a set of open pipes is used when applying the multi-load method to the intake or exhaust sides of internal combustion engines. A set of pipe lengths which cause the calculated results to be least sensitive to the input data error can be found when using open pipe loads. The present work is intended to produce guidelines for preparing an appropriate load set in order to obtain accurate source properties of fluid machines.

• Geomechanics and Engineering
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• v.24 no.3
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• pp.281-293
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• 2021

Uncertainties in geomechanical input parameters which mainly related to inappropriate data acquisition and estimation due to lack of sufficient calibration information, have led wellbore instability not yet to be fully understood or addressed. This paper demonstrates a workflow of employing Quantitative Risk Assessment technique, considering these uncertainties in terms of rock properties, pore pressure and in-situ stresses to makes it possible to survey not just the likelihood of accomplishing a desired level of wellbore stability at a specific mud pressure, but also the influence of the uncertainty in each input parameter on the wellbore stability. This probabilistic methodology in conjunction with Monte Carlo numerical modeling techniques was applied to a case study of a well. The response surfaces analysis provides a measure of the effects of uncertainties in each input parameter on the predicted mud pressure from three widely used failure criteria, thereby provides a key measurement for data acquisition in the future wells to reduce the uncertainty. The results pointed out that the mud pressure is tremendously sensitive to UCS and SHmax which emphasize the significance of reliable determinations of these two parameters for safe drilling. On the other hand, the predicted safe mud window from Mogi-Coulomb is the widest while the Hoek-Brown is the narrowest and comparing the anticipated collapse failures from the failure criteria and breakouts observations from caliper data, indicates that Hoek-Brown overestimate the minimum mud weight to avoid breakouts while Mogi-Coulomb criterion give better forecast according to real observations.