• Journal of the Korea Computer Industry Society
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• v.4 no.10
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• pp.587-598
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• 2003

This paper construct two-level word similarity relation matrices about title and to scientific treatise. As guide keyword similarity relation matrices which is constructed to co-occurrence frequency base same time keeps recall rater by query expansion by tolerance relation, it is index structure to improve the precision rate by two-level contents base retrieval. Therefore, draw area knowledge through subject analysis and reasoned user's information request and area knowledge to fuzzy logic base. This research is research to improve vocabulary mismatch problem and information expression having essentially on query.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.420-423
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• 2001

In this paper, the Multi-FNNs(Fuzzy-Neural Networks) architecture is identified and optimized using HCM(Hard C-Means) clustering method and genetic algorithms. The proposed Multi-FNNs architecture uses simplified inference and linear inference as fuzzy inference method and error back propagation algorithm as learning rules. Here, HCM clustering method, which is carried out for the process data preprocessing of system modeling, is utilized to determine the structure of Multi-FNNs according to the divisions of input-output space using I/O process data. Also, the parameters of Multi-FNNs model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model we use the time series data for gas furnace and the NOx emission process data of gas turbine power plant.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.4
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• pp.61-70
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• 1996

This paper deals with consciousn~s structure by means of human subjective judgement. Fuzzy structural modeling which is a modeling method for consciousness structure have the large number of pairwise comparigon by human subjective judgement, is difficplt to check the consistency index which denotes the precision for human judgement. To improve these points, we set the structure of consciousness by fuzzy structural modeling method using the concept of pairwise compariqon matrix in AHP. The efficiency of this method is showed by means of the consciousness structure graph to the qyality system construction.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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• pp.560-567
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• 2007

The objective of this research is to optimize the designing parameters of the parallel manipulator with large orientation workspace at the boundary position of the constant orientation workspace (COW). The method uses a simple genetic algorithm(SGA) while considering three different kinematic performance indices: COW and the global conditioning index(GCI) to evaluate the mechanism's dexterity for translational motion of an end-effector, and orientation workspace of two angle of Euler angles to obtain the large rotation angle of an end-effector at the boundary position of COW. Total fifteen cases divided according to the combination of the sphere radius of COW and rotation angle of orientation workspace are studied, and to decide the best model in the total optimized cases, the fuzzy inference system is used for each case's results. An optimized model is selected as a best model, which shows better kinematic performances compared to the basis of the pre-existing model.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.894-897
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• 2000

In this paper, we present a content-based image retrieval method that is less sensitive to some rotations and translations of an image by using the fuzzy region segmentation. The algorithm retrieves similar images from a database using the two features of color and color spatial information. To index images, we use the average coordinates of color distribution to obtain the spatial information of each segmented region. Furthermore, we also propose the alternative to the ripple phenomenon, which is occurred in the conventional fuzzy region segmentation algorithm.

• Journal of Navigation and Port Research
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• v.45 no.5
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• pp.252-258
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• 2021

Given the cyclicality, seasonality, and capital-intensiveness, the development of the shipping industry has long been contingent on corporate financing activities. As such, there have been a growing number of cities in East Asia pursuing a global maritime financial center in order to support their domestic shipping industry. However, it is widely accepted that financial services relevant to shipping in East Asia are quite under-developed compared to those of other leading maritime financial centers in Europe and North America. In this regard, this paper aimed to construct an evaluation index of maritime financial centers in terms of financial ecological environment for the purpose of highlighting the current status of development and suggesting future directions. Furthermore, this paper examined the development of shipping finance in Qingdao as a numerical example using the fuzzy comprehensive evaluation and compared results with those of Shanghai.

• Journal of Technology Innovation
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• v.19 no.3
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• pp.85-114
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• 2011

This paper aims at developing a new index that represents the Korean new growth industries, which is named the Korea Future Technology Index(KOFTI). The KOFTI is designed to provide a reliable and econometric index based on which the Korean government searches for new growth engines. The KOFTI is composed of three individual indexes such as the Economic Impact Index, the Future Strategy Index, and the Technological Influence Index. The KOFTI is applied for 62 star brands, which have been promoted by the Korean government for the korean future industrial competitiveness. The top 13 leading industries are drawn from the calculation of the KOFTI for 62 star brands.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.571-576
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• 2002

There have been a lot of considerations dealing with improving the performance of neuro-fuzzy system. The studies on the neuro-fuzzy modeling have largely been devoted to two approaches. First is to improve performance index of system. The other is to reduce the structure size. In spite of its satisfactory result, it should be noted that these are difficult to extend to high dimensional input or to increase the membership functions. We propose a novel neuro-fuzzy system based on the efficient clustering method for initializing the parameters of the premise part. It is a very useful method that maintains a few number of rules and improves the performance. It combine the various algorithms to improve the performance. The Expectation-Maximization algorithm of Gaussian mixture model is an efficient estimation method for unknown parameter estimation of mirture model. The obtained parameters are used for fuzzy clustering method. The proposed method satisfies these two requirements using the Gaussian mixture model and neuro-fuzzy modeling. Experimental results indicate that the proposed method is capable of giving reliable performance.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.441-457
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• 2011

In this study, the axiomatic design(AD) method is applied to construct the hierarchical structure of evaluation criteria and the AHP method is used to calculate the weights of criteria in order to develop the proposal evaluation index for the overseas weapon system purchasing projects. The common evaluation items as main categories are selected through the review of evaluation criteria from the previous works and projects, relevant regulations and defense policy, and the design matrix using fuzzy concept is established and evaluated by the expert group in each design phase to determine the independency, that is the satisfaction of decoupled or uncoupled design, for each criteria in the same hierarchy when they are derived from the main categories. The establishment of decoupled or uncoupled design matrix provides mutually exclusiveness of how small number of DPs can be accounted for FRs within the same hierarchy. The proposal evaluation index developed in this study will be used as a general proposal evaluation index for the overseas weapon system purchasing projects which there are no systematically established evaluation tools.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1724-1731
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• 2018

The conventional polynomial neural network (PNN) is a classical flexible neural structure and self-organizing network, however it is not free from the limitation of overfitting problem. In this study, we propose a space search-optimized polynomial neural network (ssPNN) structure to alleviate this problem. Ranking selection is realized by means of ranking selection-based performance index (RS_PI) which is combined with conventional performance index (PI) and coefficients based performance index (CPI) (viz. the sum of squared coefficient). Unlike the conventional PNN, L2-norm regularization method for estimating the polynomial coefficients is also used when designing the ssPNN. Furthermore, space search optimization (SSO) is exploited here to optimize the parameters of ssPNN (viz. the number of input variables, which variables will be selected as input variables, and the type of polynomial). Experimental results show that the proposed ranking selection-based polynomial neural network gives rise to better performance in comparison with the neuron fuzzy models reported in the literatures.