• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.300-303
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• 2003

An Algorithm based on direct implementation of variable structure systems theory approach is proposed for on-line training of multilayer perceptrons. Network structures which have multiple inputs, single output and one hidden layer are considered and the weights are assumed to have capabilities for continuous time adaptation. The zero level set of the network learning error is regarded as a sliding surface in the learning parameters space. A sliding mode trajectory can be brought on and reached in finite time on such a sliding manifold. Results from simulated on-line identification task for a two-link planar manipulator dynamics are also presented.

• Journal of Korean Society of Disaster and Security
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• v.5 no.1
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• pp.13-19
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• 2012

This paper introduces platform of platform (POP) for global network on climate adaptation change and disaster risk reduction (CCA/DRR). The POP consists of disaster prevention technology e-market platform, e-learning platform, information sharing platform, and monitoring platform for AMCDRR action plan. The POP is developing based on Korean e-Government standard framework and supports Web and mobile service. Additionally the POP uses special product and technology to search and classify data about CCA/DRR.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.187-196
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• 1996

This paper introduces the concept of fixed weights and proposes an algorithm for classification by adding this concept to vector space separation method in LVQ. The proposed algorithm is based on competitive learning. It uses fixed weightsfor generality and fast adaptation efficient radius for new weight creation, and L1 distance for fast calcualtion. It can be applied to many fields requiring adaptive learning with the support of generality, real-tiem processing and sufficient training effect using smaller data set. Recognition rate of over 98% for the train set and 94% for the test set was obtained by applying the suggested algorithm to on-line handwritten recognition.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.52-63
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• 1995

A neuro-fuzzy algorithm is presented for nuclear reactor power control in a pressurized water reactor. Automatic reacotr power control is complicated by the use of control rods because of highly nonlinear dynamics in the axial power shape. Thus, manual shaped controls are usually employed even for the limited capability during the power maneuvers. In an attempt to achieve automatic shape control, a neuro-fuzzy approach is considered because fuzzy algorithms are good at various aspects of operator's knowledge representation while neural networks are efficinet structures capable of learning from experience and adaptation to a changing nuclear core state. In the proposed neuro-fuzzy control scheme, the rule base is formulated based ona multi-input multi-output system and the dynamic back-propagation is used for learning. The neuro-fuzzy powere control algorithm has been tested using simulation fesponses of a Korean standard pressurized water reactor. The results illustrate that the proposed control algorithm would be a parctical strategy for automatic nuclear reactor power control.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1187-1188
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• 2008

An area of research called evolvable hardware has recently emerged which combines aspects of evolutionary computation with hardware design and synthesis. Evolvable hardware (EHW) is hardware that can change its own circuit structure by genetic learning to achieve maximum adaptation to the environment. In conventional EHW, the learning is executed by software on a computer. In this paper, we have studied and surveyed a gate-level evolvable hardware chip, by integrating both GA hardware and reconfigurable hardware within a single LSI chip. The chip consists of genetic algorithm(GA) hardware, reconfigurable hardware logic, and the control logic. In this paper, we describe the architecture, functions of the chip.

• Journal of Power System Engineering
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• v.5 no.2
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• pp.93-99
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• 2001

This paper presents the automatic recognition system for car number plate. In our country, two types of number plate pattern is used. The one is old type of number plate, the other is new type of number plate. To recognize both new and old type number plates, the system must have flexibility. Therefore, in this paper, automatic recognition system is developed by use of the neural network for good adaptation, good generalization, and modulation. And because the number plate is made of three codes, the multi neural network consists of three networks. Neural network is teamed by GDR(Generalized Delta learning Rule) and it is verified the effectiveness of the method through experimental results.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.449-450
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• 2007

Evolvable hardware(EHW) is a dynamic field that brings together reconfigurable hardware, artificial intelligence, fault tolerance and autonomous systems. This paper gives an introduction to the field. The features that can be used to identify and classify evolvable hardware are the evolutionary algorithm, the implementation and the genotype representation. Evolvable hardware (EHW) is hardware that can change its own circuit structure by genetic learning to achieve maximum adaptation to the environment. In conventional EHW, the learning is executed by software on a computer.

• Education of Primary School Mathematics
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• v.9 no.1 s.17
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• pp.11-29
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• 2005

Discrete mathematics is as important as it was reformed as an optional subject in the middle school and high school in the 7th national curriculum. There are a lot of studies about discrete mathematics in the middle course but studies about it in elementary course has little performed. Therefore, the purpose of this paper is to analyze the concept of discrete mathematics, which is hidden in the mathematics textbook of elementary school and to develop the learning materials of discrete mathematics. Through this, it would make the students to have the sharp insight in their daily lift and mathematical experience by learning: the mathematical inquiry and adaptation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.834-837
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• 1993

This paper describes the implementation of an autonomous fuzzy logic controller. The controller is endowed with basic control principles and learning constructs which enable it to autonomously modify its control policy based on system performance. The controller lies dormant when system response is satisfactory but if rapidly initiates adaptation in real time when adverse performance is observed. The autonomous fuzzy controller is implemented on an Intel MCS-51 series micro-controller board using an inexpensive 8-bit Intel 8031 processor. The 11.06 MHz micro-controller operates at a rate exceeding 200 "global" look-up table reinforcements per second. This is important when developing practical on-line adaptive controllers for fast systems. It is also significant because an initial controller look-up table could be incorrect or non-existent. The relatively high learning rate enables the controller to learn to control a system even while it is controlling it.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.179-182
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• 2002

In this paper, this system makes use of the analog sensor and converts the feature of fish analog signal when sensor is operating with CPU(80C196KC). Then, After signal processing, this feature Is classified a special feature and a outline of fish by using the neural network, one of the artificial intelligence scheme. This neural network classifies fish pattern of very simple and short calculation. This has linear activation function and the error backpropagation is used as a learning algorithm. And the neural network is learned in off-line process. Because an adaptation period of neural network is too long time when random initial weights are used, off-line learning Is induced to decrease the Progress time We confirmed this method has better performance than somewhat outdated machines.