• International Journal of Computer Science & Network Security
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• 제21권6호
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• pp.237-244
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• 2021

Clustering is a most powerful un-supervised machine learning techniques for division of instances into homogenous group, which is called cluster. This Clustering is mainly used for generating a good quality of cluster through which we can discover hidden patterns and knowledge from the large datasets. It has huge application in different field like in medicine field, healthcare, gene-expression, image processing, agriculture, fraud detection, profitability analysis etc. The goal of this paper is to explore both hierarchical as well as partitioning clustering and understanding their problem with various approaches for their solution. Among different clustering K-means is better than other clustering due to its linear time complexity. Further this paper also focused on data mining that dealing with high-dimensional datasets with their problems and their existing approaches for their relevancy

• 산업공학
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• 제18권3호
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• pp.253-267
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• 2005

Customer satisfaction becomes one of the important managerial concerns associated with corporate competency in current competitive environment for Internet communication service companies. Hence, it is demanding to improve a company's customer satisfaction through the total quality management perspective. In practice, engineers as well as the management hope to find major quality characteristics with Internet communication network that is closely related to customer satisfaction, consequently aiming to the raise of their company's customer satisfaction. This paper presents an empirical relationship analysis between network quality characteristics and customer satisfaction on Internet communication. Methodologically, the relationship analysis framework is based on the regression variable selection procedures. In this framework, it is implemented that; 1) iterative model building; and 2) consistent criteria application to statistical tests for selecting significant variables. A case study shows that; 1) the customer satisfaction on the network connection seems to be more closely related to the network quality characteristics compared with the customer satisfaction on the network speed; and 2) the download disconnection rate has relatively evident relationship with the customer satisfaction on the network connection.

• 한국정보통신학회논문지
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• 제6권1호
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• pp.48-54
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• 2002

인터넷 사용자와 다양한 응용의 발전에 힘입어 인터넷이 활성화되고 네트워크를 이용한 어플리케이션이 점점 더 많은 대역폭을 요구함에 따라 네트워크의 고속화를 필연적으로 수반하게 됨으로써 Gigabit Ethernet이 등장하게 되었다. Gigabit Ethernet은 기존 Ethernet 환경에서 네트워크에 대용량을 제공하고 고성능을 발휘할 수 있는 점등 여러 가지 면에서 장점을 지니고 있어 인터넷 사용자당 요구 트래픽을 해소할 수 있는 대안으로 제시되고 있다. 따라서 본 논문에서는 이러한 Gigabit Ethernet 기술과 관련하여 개념 및 특징을 살펴보고 경쟁 관계에 있는 FDDI 기술과 트래픽 분석을 통해 Gigabit Ethernet의 안정성과 효율성을 제고하였다.

• 응용통계연구
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• 제20권3호
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• pp.441-447
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• 2007

컨조인트 분석은 경영학에서 제품 대안들에 대한 소비자의 선호 정도로부터 소비자가 각 속성에 부여하는 상대적 중요도와 각 속성수준의 효용 부분가치를 추정하는 분석방법이다. 본 논문에서는 초등학교 컴퓨터 특기 적성 교육 과목들에 대한 학생들의 선호정도를 컨조인트 분석을 통해 알아보았다. 그 과정에서 특별히 인공 신경망 분석을 부가적으로 수행하면 보다 많은 유용한 지식을 얻을 수 있음을 중점적으로 다루었다.

• KIEE International Transactions on Power Engineering
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• 제3A권3호
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• pp.139-147
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• 2003

The paper presents a novel approach of constructing the state matrix of the multi-machine power system for SSR (subsynchronous resonance) analysis using the linearized equations of individual devices including electrical transmission network dynamics. The machine models in the local d-q reference frame are integrated with the network models in the common R-I reference frame by simply transforming their output equations into the R-I frame where the transformed output is used as the input to the network dynamics or vice versa. The salient feature of the formulation is that it allows for modular construction of various component models without rearranging the overall state space formulation. This universal SSR small signal stability program provides a flexible tool for systematic analyses of SSR small-signal stability impacts of both conventional devices such as generation systems and novel devices such as power electronic apparatus and their controllers. The paper also presents its application results to IEEE benchmark models.

• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1548-1555
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• 2017

This paper attempts to employ and investigate neural based approaches as interpolation tools for modeling of Switched Reluctance Motor (SRM) drive. Precise modeling of SRM is essential to analyse the performance of control strategies for variable speed drive application. In this work the suitability of Generalized Regression Neural Network (GRNN) and Extreme Learning Machine (ELM) in addition to conventional neural network are explored for improving the modeling accuracy of SRM. The neural structures are trained with the data obtained by modeling of SRM using Finite Element Analysis (FEA) and the trained neural network is incorporated in the model of SRM drive. The results signify the modeling accuracy with GRNN model. The closed loop drive simulation is performed in MATLAB/Simulink environment and the closeness of the results in comparison with the experimental prototype validates the modeling approach.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제11B권2호
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• pp.15-21
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• 2001

This paper presents an improved characteristic analysis methodology for a 5-phase hybrid stepping motor. The basic approach is based on the use of equivalent magnetic circuit taking into account the localized saturation throughout the hybrid stepping motor. The finite element method(FEM) is used to generate the magnetic circuit parameters for the complex stator and rotor teeth and airgap considering the saturation effects in tooth and poles. In addition, the neural network is used to map a change of parameters and predicts their approximation. Therefore, the proposed method efficiently improves the accuracy of analysis by using the parameter characterizing localized saturation effects and reduces the computational time by using the neural network. An improved circuit model of 5-phase hybrid stepping motor is presented and its application is provided to demonstrate the effectiveness of the proposed method.

• 터널과지하공간
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• 제8권4호
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• pp.342-350
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• 1998

시추공 텔레뷰어에 의해 획득된 시추공벽 영상을 이용하여 암반내 절리 구조 특성을 해석하고자 하였다. 절리구조의 특성으로서 발달된 절리군의 방향성 및 거칠기의 산정은 영상분석을 통한 절리궤적의 추적에 의하였으며, 산정된 절리군의 JRC 값과 추정된 역학적 상수들로부터 Barton-Bandis 모델에 의해 절리강성을 추정하고 자료들을 종합하여 암반 수치해석 모델링용 절리구조도를 작성하였다. 시추공벽 절리궤적의 추적 효율성을 높이기 위하여 영상 분석기에 내장된 함수를 이용한 최적의 매크로 프로그램과 걸칠기 산정 프로그램, 절리구조도 작성용 프로그램을 완성하였다.

• Journal of Information Processing Systems
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• 제19권5호
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• pp.576-589
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• 2023

To upgrade home style recommendations and user satisfaction, this paper proposes a personalized and optimized recommendation algorithm for interior design style based on local social network, which includes data acquisition by three-dimensional (3D) model, home-style feature definition, and style association mining. Through the analysis of user behaviors, the user interest model is established accordingly. Combined with the location-based social network of association rule mining algorithm, the association analysis of the 3D model dataset of interior design style is carried out, so as to get relevant home-style recommendations. The experimental results show that the proposed algorithm can complete effective analysis of 3D interior home style with the recommendation accuracy of 82% and the recommendation time of 1.1 minutes, which indicates excellent application effect.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2002년도 봄 학술발표회 논문집
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• pp.651-656
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• 2002

In general, the most important problem in slope stability analysis is that there is no definite way to describe the natural three-dimensional Joint network. Therefore, the many approaches were tried to anlayze the slope stability. Numerical modeling approach is one of the branch to resolve the complexity of natural system. UDEC, FLAC, and SWEDGE are widely used commercial code for the purpose on stability analysis. For the purpose on the more appropriate application of these kind of code, however, three-dimensional distribution of joint network must be identified in more explicit way. Remaining problem is to definitely describe the three dimensional network of joint and bedding, but it is almost impossible in practical sense. Three dimensional joint generation method with random number generation and the results of generation to UDEC have been applied to settle the refered problems in field site. However, this approach also has a important problem, and it is that joint network is generated only once. This problem lead to the limitation on the application to field case, in practical sense. To get rid of this limitation, Monte Carlo Simulation is proposed in this study 1) statistical analysis of input values and definition of the applied system with statistical parameter, 2) instead of the consideration of generated network as a real system, generated system is just taken as one reliable system, 3) present the design parameters, through the statistical analysis of ouput values Results of this study are not only the probability of failure, but also area of failure block, shear strength, normal strength and failure pattern, and all of these results are described in statistical parameters. The results of this study, shear strength, failure area, pattern etc, can provide the direct basement on the design, cutoff angle, support pattern, support strength and etc.