• Journal of Information Technology Applications and Management
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• v.14 no.2
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• pp.151-168
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• 2007

The corporate credit rating represents an assessment of the relative level of risk associated with the timely payments required by the debt obligation. In this study, the corporate credit rating model employs artificial intelligence methods including Neural Network (NN) and Case-Based Reasoning (CBR). At first we suggest three classification models, as partitioned neural networks, all of which convert multi-group classification problems into two group classification ones: Ordinal Pairwise Partitioning (OPP) model, binary classification model and simple classification model. The experimental results show that the partitioned NN outperformed the conventional NN. In addition, we put to use CBR that is widely used recently as a problem-solving and learning tool both in academic and business areas. With an advantage of the easiness in model design compared to a NN model, the CBR model proves itself to have good classification capability through the highest hit ratio in the corporate credit rating.

• Communications of Mathematical Education
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• v.22 no.3
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• pp.369-382
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• 2008

We discuss the effect of ability grouping calculus courses based upon student's proficiency of the subject and their collective examination of midterms and finals among mid-level and low-level classes. We assess incoming freshmen at Seoul National University of Technology(SNUT) of their proficiency in calculus and assign them to the appropriate levels within the course(i.e., high-level, mid-level, low-level). We found that this was beneficial to both students and instructors. Instructors can easily determine the pace in which each class should be kept, and students can quickly adapt to the learning environment.

• Journal of Korea Technology Innovation Society
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• v.5 no.1
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• pp.1-15
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• 2002

This study reviews the new Perspectives of science and technology Policy based on "the innovation system ap-proach" . It examines the theories of innovation and the economic rationale of government intervention of the in-novation system approach and compares them with those of traditional nee-classical approach. It also examines the basic theme of science and technology Policy of "the innovation system approach" It argues that the enhancement of innovating capability, the transformation of innovation system coping with changing technological and econom-ic environments, and the policy learning of the government and innovators are very important and peculiar sub-jects of the science and technology Policy based on "the innovation system approach".ovation system approach".uot;.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.592-600
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• 2006

The pattern recognition of the complicated grasping operation based on electroencephalography (simply named as EEG) is very helpful on realtime control of the robotic hand. In the paper, a new spectral feature analysis method based on Band Pass Filter (simply named as BPF) and Power Spectral Analysis (simply named as PSA) is presented for discriminating the complicated grasping operations. By analyzing the spectral features of grasping operations with the use of the two-channel EEG measurement system and the pattern recognition of the BP neural network, the degree of recognition by the traditional spectral feature method based on FFT and the new spectral features method based on BPF and PSA could be compared. The results show that the proposed method provides highly improved performance than the traditional one because the new method has two obvious advantages such as high recognition capability and the fast learning speed.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.3
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• pp.229-237
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• 2001

In this paper, we propose two design methods of neural networks controller for the height control of helicopter, one is the design of neural network controller having learning capability and the other is the design of more improved neural network controller. Through the simulation results, we show that the proposed controllers have controllers have enhanced control performance(rapid response, effectiveness and safety) than the typical neural networks controller in the height control of helicopter.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.34D no.6
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• pp.65-74
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• 1997

In this paper, SA-multiplexed filter is designed using SA (simulated ananealing) to recognize music notation patterns varying in size, shape, position and having considerably many similar shapes for optical pattern recognition system. This filter has correlation resutls at wanted location and can identify same class, classify similar class for scale-varianted or rotation-varianted music notation patterns havng learning process. Also, the optimum filter is oriented to analyze on the similar discrimination at acquired position using SA and enhances optical diffractive efficiency as well as peak beam intensity. Compared with POF *(phase only filter), cosine-BPOF(cosine-binary phase only filter), that has excellent discrimination capability even if the different rate is 0.1% quantitatively.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.82-89
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• 1997

In this paper, an adaptive speed controller with an FNN(Feedforward Neural Network) is proposed for servo motor drives. Generally, the motor system has nonlinearities in friction, load disturbance and magnetic saturation. It is necessary to treat the nonlinearities for improving performance in servo control. The FNN can be applied to control and identify a nonlinear dynamical system by learning capability. In this study, at first, a robust speed controller is developed by Lyapunov stability theory. However, the control input has discontinuity which generates an inherent chattering. To solve the problem and to improve the performances, the FNN is introduced to convert the discontinuous input to continuous one in error boundary. The FNN is applied to identify the inverse dynamics of the motor and to control the motor using coordination of feedforward control combined with inverse motor dynamics identification. The proposed controller is developed for an SR motor which has highly nonlinear characteristics and it is compared with an MRAC(Model Reference Adaptive Controller). Experiments on an SR motor illustrate te validity of the proposed controller.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.465-467
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• 1995

High impedance fault can not be easily detected by conventional method. But if it would not be detected and cleared quickly, it can result in fires, and electric shock. In this paper, ANN, which has learning capability, is used for high impedance fault detection. The potential of the neural network approach is demonstrated by simulation using KEPCO's measured data. Among ANN models used in this paper, CPN shows better result than BPN in respect of convergence and reliability.

• Journal of the Korean Institute of Intelligent Systems
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• v.4 no.1
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• pp.35-49
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• 1994

It is well known that, for nominimum phase systems, a conventional linear controller of PID type or an adaptive controller of this structure shows limitation in achieving a satisfactory performance under tight specifications. In this paper, we combine a neuro-controller with a PI-controller with off-line learning capability provided by the Genetic Algorithm to propose a novel neuro-controller to control nonminimum phase systems effectively. The simulation results show that our proposed model is more efficient with faster rising time and less undershoot effect when the performances of the proposed controller and a conventional form are compared.

• The Journal of Fisheries Business Administration
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• v.33 no.1
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• pp.19-41
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• 2002

Recently, the number of Internet shopping malls increases dramatically Internet shopping malls offer direct sales by electronic catalogs. As compared with to physical stores and paper catalogs, electronic catalogs differ in terms of the varieties and types of products offered, promotional efforts, service, interface, ordering and delivering, and so on. This paper analysed the features of electronic catalogs for fisheries by 45 variables. By descriptive statistics of electronic catalogs for fisheries, most electron)c catalogs had sufficient product related information. But promotion and transaction security related features were scarce. And some development technologies of electronic catalogs for fisheries were obsolete. By factor analysis, there were 9 factors of electronic catalogs for fisheries, that was, design of product pages, transaction information, playfulness, convenience of product selection, interface design, design of homepages, product information, learning capability, other electronic catalog related factor. Thus in standardizing electronic catalog for fisheries products, the above 9 factors should be reflected significantly.