• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.247-250
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• 2001

In this paper, we propose an growing and pruning algorithm to design the adaptive structure of modular wavelet neural network(MWNN) with F-projection and geometric growing criterion. Geometric growing criterion consists of estimated error criterion considering local error and angle criterion which attempts to assign wavelet function that is nearly orthogonal to all other existing wavelet functions. These criteria provide a methodology that a network designer can constructs wavelet neural network according to one's intention. The proposed growing algorithm grows the module and the size of modules. Also, the pruning algorithm eliminates unnecessary node of module or module from constructed MWNN to overcome the problem due to localized characteristic of wavelet neural network which is used to modules of MWNN. We apply the proposed constructing algorithm of the adaptive structure of MWNN to approximation problems of 1-D function and 2-D function, and evaluate the effectiveness of the proposed algorithm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.130-133
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• 2000

In this paper, a new design methodology named FNNN(Fuzzy Polynomial Neural Network) algorithm is proposed to identify the structure and parameters of fuzzy model using PNN(Polynomial Neural Network) structure and a fuzzy inference method. The PNN is the extended structure of the GMDH(Group Method of Data Handling), and uses several types of polynomials such as linear, quadratic and modified quadratic besides the biquadratic polynomial used in the GMDH. The premise of fuzzy inference rules defines by triangular and gaussian type membership function. The fuzzy inference method uses simplified and regression polynomial inference method which is based on the consequence of fuzzy rule expressed with a polynomial such as linear, quadratic and modified quadratic equation are used. Each node of the FPNN is defined as fuzzy rules and its structure is a kind of neuro-fuzzy architecture Several numerical example are used to evaluate the performance of out proposed model. Also we used the training data and testing data set to obtain a balance between the approximation and generalization of proposed model.

• Bulletin of the Korean Chemical Society
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• v.29 no.4
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• pp.817-821
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• 2008

We have investigated the influence of the crystal structure on the chemical bonding nature and photocatalytic activity of cubic and hexagonal perovskite A[$Cr_{1/2}Ta_{1/2}$]O3 (A = Sr, Ba) compounds. According to neutron diffraction and field emission-scanning electron microscopy, the crystal structure and particle size of these compounds are strongly dependent on the nature of A-site cations. Also, it was found that the face-shared octahedra in the hexagonal phase are exclusively occupied by chromium ions, suggesting the presence of metallic (Cr-Cr) bonds. X-ray absorption and diffuse UV-vis spectroscopic analyses clearly demonstrated that, in comparison with cubic Sr[$Cr_{1/2}Ta_{1/2}$]$O_3$ phase, hexagonal Ba[$Cr_{1/2}Ta_{1/2}$]$O_3$ phase shows a decrease of Cr oxidation state as well as remarkable changes in interband Cr d-d transitions, which can be interpreted as a result of metallic (Cr-Cr) interactions. According to the test of photocatalytic activity, the present semiconducting materials have a distinct activity against the photodegradation of 4-chlorophenol. Also the Srbased compound was found to show a higher photocatalytic activity than the Ba-based one, which is attributable to its smaller particle size and its stronger absorption in visible light region.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.378-382
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• 2011

This paper develops the core competencies of manufacturing workers, analyze the consciousness structure on the core competencies. As the analyzing method of consciousness structure, ISM(Interpretive Structural Modeling) and FSM(Fuzzy Structural Modeling) are used to classify layers and determine the connection state. However, the element of each layer is frequently changed by data. This paper suggests the method with the point of view that the structure is determined basically and the connection state of the structure model is changeable depending on the method; first to determine structure model by ISM, second to determine connection by FSM. By using this method, the objective structure model, analyzing the consciousness on the core competencies of manufacturing workers, is suggested with specialist confirm.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.4
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• pp.102-108
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• 2010

Projection microstereolithography is a process of fabricating a micro-structure by using dynamic mask such as digital micromirror device(DMD). DMD shapes the beam into cross-sectional image of structure. Photocurable resin is cured by the beam and stacked layer on top of layer. It is difficult to deliver the beam from the DMD to the photocurable resin without any distortions. We assume that the beam exposed to the resin by 1 pixel of DMD has Gaussian distribution, so the shaped beam reflected by the DMD affects its neighboring area. Curing pattern corresponding to a cross-sectional images is predicted by superposition of pixels of Gaussian distribution and it is similar to cured shape.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.572-575
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• 2004

Since the 1990s, the advancement of semiconductor technology has resulted in the development of microprocessor technology, auxiliary computer technology, and application technology such as intelligent algorithms (neural network, fuzzy, etc.). These based the development of intelligent machines. An agent is autonomous software that recognizes environment, exchanges knowledge with other agents and makes decisions. We designed agent-based sensor structure. For the purpose, first, it modeled the function of an intelligent machine. Second, it designed sensory function on the agent level.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.302-305
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• 1996

In this paper, an optimal identification method using fuzzy-neural networks is proposed for modeling of nonlinear complex systems. The proposed fuzzy-neural modeling implements system structure and parameter identification using the intelligent schemes together with optimization theory, linguistic fuzzy implication rules, and neural networks(NNs) from input and output data of processes. Inference type for this fuzzy-neural modeling is presented as simplified inference. To obtain optimal model, the learning rates and momentum coefficients of fuzz-neural networks(FNNs) and parameters of membership function are tuned using genetic algorithm(GAs). For the purpose of its application to nonlinear processes, data for route choice of traffic problems and those for activated sludge process of sewage treatment system are used for the purpose of evaluating the performance of the proposed fuzzy-neural network modeling. The show that the proposed method can produce the intelligence model w th higher accuracy than other works achieved previously.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1137-1140
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• 1993

A dynamic-structure system is one that has the flexibility to change the system configuration automatically so as to operate in an optimal manner. A conceptural model for a dynamic-structure system is presented in this paper. In this model, the interchangeable components of the overall system are grouped together. Their activity levels are evaluated by an intelligent preprocessor that is associated with the group. A knowledge-based task distribution system evaluates the activity levels and makes decisions as to how the components operating below capacity should be shared with workcells that have similar components that are overloaded. Associated decision making can be effected through fuzzy logic and particularly the compositional rule of inference. A simulation example is given to illustrate the application of dynamic structuring.

• International Journal of Railway
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• v.7 no.3
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• pp.80-84
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• 2014

The purpose of this paper was to review Intelligent Compaction (IC) techniques, which is regarded relatively new to the railroad roadbed construction activity. Most of civil structures are built on roadbed that supposed to provide adequate load bearing support to the upper structure through the qualified compaction process. However, it is not uncommon for structure failure attributed to inadequate compaction control take place in field sites. Unlike traditional compaction control method to check field density at several locations, IC techniques continuously measure various compaction quality indices that represent compaction uniformity. In this paper, a series of literature review relevant to IC techniques was conducted to provide concise summary on the following categories: 1) background of IC technique; 2) Summary of IC vendors and basic principles; 3) modeling of IC behavior, and 4) case study along with correlation between IC with other measurements. In summary, IC technologies seem to be promising in future railroad construction to achieve better compaction quality control so that the serviceability of railroad can be ensured with minimizing rehabilitation and maintenance activities.

• 한국ITS학회:학술대회논문집
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• v.2006 no.10
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• pp.316-320
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• 2006