• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.538-544
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• 1999

In this paper, we propose a new fault detection algorithm for transmission line protection using ANFIS(Adaptive Network Fuzzy Inference System). The developed system consists of two subsystems: fault type classification, and fault location estimation. We use rms value, zero sequence component and positive sequence of current, and then using learning method of neural network, premise and consequent parameters are tuned properly. To prove the performance of the proposcd system, generated data by EMTP(Electr0- Magnetic Transient Program) sin~ulationi s used. It is shown that the proposed relaying classifies fault types accurately and advances fault location estimation.

• Annals of Fuzzy Mathematics and Informatics
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• v.16 no.3
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• pp.337-361
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• 2018

We introduce and study some basic properties of rough $I_{\lambda}$-statistical convergent of weight g (A), where $g:{\mathbb{N}}^3{\rightarrow}[0,\;{\infty})$ is a function statisying $g(m,\;n,\;k){\rightarrow}{\infty}$ and $g(m,\;n,\;k){\not{\rightarrow}}0$ as $m,\;n,\;k{\rightarrow}{\infty}$ and A represent the RH-regular matrix and also prove the Korovkin approximation theorem by using the notion of weighted A-statistical convergence of weight g (A) limits of a triple sequence of Bernstein-Stancu polynomials.

• Journal of the Korea Convergence Society
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• v.4 no.3
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• pp.35-41
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• 2013

Grouping problem with similarities between DNA sequences are studied. The similaritymeasure and the distance measure showed the complementary characteristics. Distance measure can be obtained by complementing similarity measure, and vice versa. Similarity measure is derived and proved. Usefulness of the proposed similarity measure is applied to grouping problem of 25 cockroach DNA sequences. By calculation of DNA similarity, 25 cockroaches are clustered by four groups, and the results are compared with the previous neighbor-joining method.

• Korean Journal of Construction Engineering and Management
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• v.14 no.4
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• pp.140-151
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• 2013

In 2011 and 2012, Korean construction firms awarded around $ 64.5. Billion each year from the overseas market in 2011. This contract value accounted for overwhelming portion of total overseas construction contract values, and this growth is expected to continue for the next decade. However, contract scopes awarded to the Korean construction firms mainly involve detailed design and construction phases due to their competitiveness for the construction techniques. In other words, front-end-engineering-design and construction project management are not considered part of core business due to the lack of project management skills and experience. The researchers focused on development of construction sequence model required to improve construction planning and scheduling skills for the Korean construction firms. The model identifies critical work items and the sequence throughout project execution process. In addition, the researchers developed a risk evaluation method by applying fuzzy theory to the critical construction activities for the industrial plant construction projects. Developed methodology will help project practitioners to develop project schedule in a timely and effe ctive manner and evaluate project risks associated with scheduling process for the industrial plant construction projects.

• The KIPS Transactions:PartB
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• v.19B no.1
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• pp.19-26
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• 2012

The rapid increase of information imposes new demands of content management. The purpose of automatic audio segmentation and classification is to meet the rising need for efficient content management. With this reason, this paper proposes a high-accuracy algorithm that segments audio signals and classifies them into different classes such as speech, music, silence, and environment sounds. The proposed algorithm utilizes support vector machine (SVM) to detect audio-cuts, which are boundaries between different kinds of sounds using the parameter sequence. We then extract feature vectors that are composed of statistical data and they are used as an input of fuzzy c-means (FCM) classifier to partition audio-segments into different classes. To evaluate segmentation and classification performance of the proposed SVM-FCM based algorithm, we consider precision and recall rates for segmentation and classification accuracy for classification. Furthermore, we compare the proposed algorithm with other methods including binary and FCM classifiers in terms of segmentation performance. Experimental results show that the proposed algorithm outperforms other methods in both precision and recall rates.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.4
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• pp.451-456
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• 1999

All the teaching items in a textbook are normally arranged in a prescribed teaching order. However, one can easily find that the textbooks of the same kind, even with the same teaching items, show different arrangements. Without learning preceding teaching items, students may have a difficulty in understanding the teaching items. In this sense, it is very important to decide how to arrange teaching items in terms of teaching sequence. As a solution to this problem, lsamu Matsubara presents a method based on the graph theory. The four types defined in his method are the straight type, the group type, the branch type, and the independent type. Among these, the three types except the straight type lack the objectivity. An objective solution to these three types, based on the fuzzy theory. is propopsed in this paper.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.3
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• pp.210-216
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• 2006

In the rule based modeling, data partitioning plays crucial role be cause partitioned sub data set implies particular information of the given data set or system. In this paper, we present an empirical study result of the data pattern estimation to find underlying data patterns of the given data. Presented method performs crisp type clustering with given n number of data samples by means of the sequential agglomerative hierarchical nested model (SAHN). In each sequence, the average value of the sum of all inter-distance between centroid and data point. In the sequel, compute the derivation of the weighted average distance to observe a pattern distribution. For the final step, after overall clustering process is completed, weighted average distance value is applied to estimate range of the number of clusters in given dataset. The proposed estimation method and its result are considered with the use of FCM demo data set in MATLAB fuzzy logic toolbox and Box and Jenkins's gas furnace data.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.117-127
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• 1995

In this paper, we suggest a motion analysis method using ART-I1 competitive learning neural network and fuzzy reasoning by matching the same objects through the consecutive image sequence. we use the size and mean intensity of the region obtained from image segmentation for the region matching by the region and use a ART-I1 competitive learning neural network wh~ch has a learning ability to reflect the topology of the input patterns in order to select characteristic points to describe the shape of a region. Motion vectors for each regions are obtained by matching selected characteristic points. However, the two dimensional image, the projection of the the three dimensional real world, produces fuzziness in motion analysis due to its incompleteness by nature and the error from image segmentation used for extracting information about objects. Therefore, the belief degrees for each regions are calculated using fuzzy reasoning to l-nanipulate uncertainty in motion estimation.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.4
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• pp.15-20
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• 2005

If we can forecast the replacement time of engine oil, we extend the life-time of our engine and increase the continued ratio. But, the replacement times of engine oil is influenced by the following elements: the distance that cars or vehicles travel, vehicles that run a short range, types of engine oil etc. that run a long distance. In this paper, We forecast engine oil replacement times by using fuzzy neural network algorithm. This algerian uses the data of distance covered, color of engine oil etc. Through a sequence of simulation, the exchange system of intelligence style engine oil decides on the replacement times of engine oil quite accurately. Therefore, We expect vehicles to become more convenient if the above algorithm is a lied to the present types of cars.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.79-92
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• 2002

This paper describes a research work of developing computer-aided design of a product with bending and piercing for progressive working. An approach to the system for progressive working is based on the knowledge-based rules. Knowledge for the system is formulated from plasticity theories, experimental results and the empirical knowledge of field experts. The system has been written in AutoLISP on the AutoCAD with a personal computer and is composed of four main modules, which are input and shape treatment, flat pattern layout, strip layout and die layout modules. The system is designed by considering several factors, such as bending sequences by fuzzy set theory, complexities of blank geometry, punch profiles, and the availability of a press equipment. Strip layout drawing generated in the strip layout module is presented in 3-D graphic farms, including bending sequences and piercing processes with punch profiles divided into for external area. The die layout module carries out die design for each process obtained from the results of the strip layout. Results obtained using the modules enable the manufacturer for progressive working of electric products to be more efficient in this field.