• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.311-314
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• 2003

In radar tracking, since the sensor measures range, azimuth and elevation angle of a target, the measurement equation is nonlinear and the extended Kalman filter (EKF) is applied to nonlinear estimation. The conventional EKF has been widely used as a nonlinear filter for radar tracking, but the considerably large measurement error due to the linearization of nonlinear function in highly nonlinear situations may deteriorate the performance of the EKF. To solve this problem, a fuzzy-model-based Kalman filter (FMBKF) is proposed for radar tracking. The FMBKP uses a local model approximation based on a TS fuzzy model instead of a Jacobian matrix to linearize nonlinear measurement equation. The hybrid GA and RLS method is used to identify the premise and the consequent parameters and the rule numbers of this TS fuzzy model. In two-dimensional radar tracking problem, the proposed method is compared with the conventional EKF.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.100-103
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• 2002

사례 기반 추론(case-based reasoning)은 과거에 유사하게 수행된 적이 있는 사레를 유추하고, 유추된 사례의 해를 이용하여 현재의 문계를 해결하는 기법으로서 규칙 기반 추론과 함께 여러 분야에 이용되고 있다. 하지만 사례기반 추론시 사레베이스로부터의 유사성에 근거한 검색을 해야 하므로 사례베이스의 크기가 증가하게 되면 검색시간이 길어지게 되거나 적절하지 못한 사레가 조회될 수 있다 특히 사레베이스 내의 모든 사례에 대하여 유사도를 계산하게 되기 때문에 수행속도가 현저히 저하되는 문제점을 지니고 있다. 본 논문에서는 규칙 및 퍼지 클러스터링에 의한 사레기반추론을 이용한 E-FFIS(Enhanced-Fire Fighting Intelligent System)를 제안한다. 제안하는 시스템은 기존의 H-FFIS(Hybrid-Fire fighting Intelligent System)와 비교해 보았을 때 수행시간을 감소시키면서 정확성을 높이게 되었다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.585-590
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• 1998

The purpose of this paper is to develop a neurofuzzy modeling & inference system which can determine principle dimensions and hull factors in an initial ship design. Neurofuzzy modeling & inference for a hull form design (NeFHull) applies the given input-output data to the fuzzy theory. NeFHull also deals the fuzzificated values with neural networks. NeFHull redefines normalized input-output data as membership functions and executes the fuzzficated information with backporpagation-neural -networks. A hybrid learning algorithms utilized in the training of neural networks and examining the usefulness of suggested method through mathematical and mechanical examples.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.1
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• pp.45-53
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• 1997

This paper presents hybrid expert system for diagnosis of electric power transformer faults. The expert system diagnose and detect faults in oil-filled power transformers based on dissolved gas analysis. As the preprocessing stage, fuzzy information theory is used to manage the uncertainty in transformer fault diagnosis using dissolved gas analysis. The Kohonen neural network takes the interim results by applying fuzzy informations theory as inputs, and performs the transformer fault diagnosis. The Proposed system tested gas records of power transformers from Korea Electric Power Corporation to verify the diagnosis performance of transformer faults.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.73-82
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• 2013

In pattern classification, feature selection is an important factor in the performance of classifiers. In particular, when classifying a large number of features or variables, the accuracy and computational time of the classifier can be improved by using the relevant feature subset to remove the irrelevant, redundant, or noisy data. The proposed method consists of two parts: a wrapper part with an improved genetic algorithm(GA) using a new reproduction method and a filter part using mutual information. We also considered feature selection methods based on mutual information(MI) to improve computational complexity. Experimental results show that this method can achieve better performance in pattern recognition problems than other conventional solutions.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.571-574
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• 2005

In this paper, we propose an efficient image segmentation technique for large-sized monochrome images using a hybrid approach which combines threshold and region-based techniques. First, an image is partitioned into fixed-size blocks and for each block the representative intensity is determined by averaging pixel intensities within the block. Next, the neighborhood blocks that have similar characteristics with respect to a specific threshold are merged in order to form candidate regions. Finally, those candidate regions are refined to get final target object regions by merging regions considering the spatial locality and certain criteria. We have performed experiments on images selected from various domains and showed that our technique was able to extract target object regions appropriately from most images.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.287-295
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• 2010

Based on the interval-valued intuitionistic fuzzy hybrid geometric (IIFHG) operator and the interval-valued intuitionistic fuzzy weighted geometric (IIFWG) operator, we investigate the group decision making problems in which all the information provided by the decision-makers is presented as interval-valued in tuitionistic fuzzy decision matrices where each of the elements is characterized by interval-valued intuitionistic fuzzy numbers, and the information about attribute weights is partially known. Anumerical example is used to illustrate the applicability of the proposed approach.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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• pp.159-167
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• 2003

This study suggests the hybrid fault diagnosis method of signed digraph (SDG) and partial least squares (PLS). SDG offers a simple and graphical representation for the causal relationships between process variables. The proposed method is based on SDG to utilize the advantage that the model building needs less information than other methods and can be performed automatically. PLS model is built on local cause-effect relationships of each variable in SDG. In addition to the current values of cause variables, the past values of cause and effect variables are inputted to PLS model to represent the Process armies. The measured value and predicted one by dynamic PLS are compared to diagnose the fault. The diagnosis example of CSTR shows the proposed method improves diagnosis resolution and facilitates diagnosis of masked multiple-fault.

• IE interfaces
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• v.18 no.4
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• pp.431-443
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• 2005

This paper describes a web-based system called DESIGNER for the analysis and design for automated material handling equipment(MHE) applications in manufacturing. DESIGNER models the processes for system integration, economic analysis, performance analysis, and automated storage/retrieval system(AS/RS) design. Based on the information specified by users, the various analysis modules are invoked to meet the needs of the material handling applications. The results of the analyses provide system users with useful data for material handling system design and decision on investment in automated MHE. Example problems are also presented to demonstrate the use of the system.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11S
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• pp.3299-3308
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• 1999

One of the most important prerequisites for a successful software process is the collaboration and software requirements negotiation of all stakeholders in the software development process. Remote users using computer networks can negotiate software requirements by computer supported system, and can share their informations. The goal of software requirements negotiation system is an integration of all win conditions and an agreement after resolution of conflicts. The existing systems need an exclusive system and must be dependent on specific platform and network. Users must have the knowledge of all stakeholder's status and use homogeneous collaborating applications. This paper presents the Web-based software requirements negotiation system for the purpose of resolution of the existing systems' problems. The Web-based software requirements negotiation system can be driven by WinWin Spiral model, and it is based on hybrid execution method. The proposed system is validated and tested on heterogeneous environments.