• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 D
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• pp.2367-2369
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• 2004

It is well known that an indirect methanol based fuel cell system imposes a performance limitation on the fuel cell electric vehicle (FCEV) due to the reformer lag. An optional battery system can be used together with fuel cell to improve this performance limitation and it is called a fuel cell hybrid electric vehicle (FCHEV) this paper first describes the configuration of FCHEV with explanation of the energy flow between subsystems. Mathematical modeling of each subsystem such as a fuel cell system, a battery system, a driving motor with the transmission are formulated and coded using Matlab/simulink software. It is illustrated by simulation results that fuel cell modeling yields appropriate stack voltage in order to get the required current quantity with varying hydrogen flow.

• 한국정보시스템학회지:정보시스템연구
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• 제14권1호
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• pp.41-65
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• 2005

The credit ration is a significant area of financial management which is of major interest to practitioners, financial and credit analysts. The components of credit rating are identified decision models are developed to assess credit rating an the corresponding creditworthiness of firms an accurately ad possble. Although many early studies demonstrate a priori which of these techniques will be most effective to solve a specific classification problem. Recently, a number of studies have demonstrate that a hybrid model integration artificial intelligence approaches with other feature selection algorthms can be alternative methodologies for business classification problems. In this article, we propose a hybrid approach using rough set theory as an alternative methodology to select appropriate attributes for case-based reasoning. This model uses rough specific interest lies in lthe stable combining of both rough set theory to extract knowledge that can guide dffective retrevals of useful cases. Our specific interest lies in the stable combining of both rough set theory and case-based reasoning in the problem of corporate credit rating. In addition, we summarize backgrounds of applying integrated model in the field of corporate credit rating with a brief description of various credit rating methodologies.

• 한국소음진동공학회논문집
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• 제12권8호
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• pp.598-608
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• 2002

This paper shows the optimal design methodology for the fluid engine mount by the artificial life algorithm. The design has been commonly modified by trial and error because there is many design parameters that can be varied in order to minimize transmissibility at the desired fundamental resonant and notch frequencies. The application of trial and error method to optimization of the fluid mount is a great work. Many combinations of parameters are possible to give us the desired resonant and notch frequencies, but the question is which combination Provides the lowest resonant peak and notch depth. In this study the enhanced artificial life algorithm is applied to get the desired fundamental resonant and notch frequencies of a fluid mount and to minimize transmissibility at these frequencies. The present hybrid algorithm is the synthesis of and artificial life algorithm with the random tabu (R-tabu) search method. The hybrid algorithm has some advantages, which is not only faster than the conventional artificial life algorithm, but also gives a more accurate solution. In addition, this algorithm can find all globa1 optimum solutions. The results show that the performance of the optimized mount compared with the original mount is improved significantly.

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.559-568
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• 2014

Induction motors are critical components in industrial processes since their failure usually lead to an unexpected interruption at the industrial plant. The studies of induction motor behavior during abnormal conditions and the possibility to diagnose different types of faults have been a challenging topic for many electrical machine researchers. In this regard, an efficient and new method to detect the induction motor-fault may be the application of the Time Synchronous Averaging (TSA) to the stator current Park's Vector. The aim of this paper is to present a methodology by which defects in a three-phase wound rotor induction motor can be diagnosed. By exploiting the cyclostationarity characteristics of electrical signals, the TSA method is applied to the stator current Park's Vector, allowing the monitoring of the induction motor operation. Simulation and experimental results are presented in order to show the effectiveness of the proposed method. The obtained results are largely satisfactory, indicating a promising industrial application of the hybrid Park's Vector-TSA approach.

• International Journal of Naval Architecture and Ocean Engineering
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• 제13권1호
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• pp.321-339
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• 2021

Response Surface Method (RSM) has been widely used for flammable cloud size prediction as it can reduce computational intensity for further Explosion Risk Analysis (ERA) especially during the early design phase of offshore platforms. However, RSM encounters the overfitting problem under very limited simulations. In order to overcome the disadvantage of RSM, Bayesian Regularization Artificial Neural (BRANN)-based model has been recently developed and its robustness and efficiency have been widely verified. However, for ERA during the early design phase, there seems to be room to further reduce the computational intensity while ensuring the model's acceptable accuracy. This study aims to develop an integrated method, namely the combination of Center Composite Design (CCD) method with Bayesian Regularization Artificial Neural Network (BRANN), for flammable cloud size prediction. A case study with constant and transient leakages is conducted to illustrate the feasibility and advantage of this hybrid method. Additionally, the performance of CCD-BRANN is compared with that of RSM. It is concluded that the newly developed hybrid method is more robust and computational efficient for ERAs during early design phase.

• International Journal of Computer Science & Network Security
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• 제23권11호
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• pp.190-194
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• 2023

By looking the importance of communication, data delivery and access in various sectors including governmental, business and individual for any kind of data, it becomes mandatory to identify faults and flaws during cyber communication. To protect personal, governmental and business data from being misused from numerous advanced attacks, there is the need of cyber security. The information security provides massive protection to both the host machine as well as network. The learning methods are used for analyzing as well as preventing various attacks. Machine learning is one of the branch of Artificial Intelligence that plays a potential learning techniques to detect the cyber-attacks. In the proposed methodology, the Decision Tree (DT) which is also a kind of supervised learning model, is combined with the different cross-validation method to determine the accuracy and the execution time to identify the cyber-attacks from a very recent dataset of different network attack activities of network traffic in the UNSW-NB15 dataset. It is a hybrid method in which different types of attributes including Gini Index and Entropy of DT model has been implemented separately to identify the most accurate procedure to detect intrusion with respect to the execution time. The different DT methodologies including DT using Gini Index, DT using train-split method and DT using information entropy along with their respective subdivision such as using K-Fold validation, using Stratified K-Fold validation are implemented.

• 대한교통학회지
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• 제30권1호
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• pp.19-30
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• 2012

하루 동안 발생하는 교통수요는 대부분 특정 시간대에 집중됨으로써 수요 및 편익 산정에 어려움을 초래한다. 따라서 보다 신뢰성 높은 결과를 산출하기 위해서는 시간대별 특성을 고려할 필요가 있다. 이를 위한 첨두/비첨두의 1시간 통행량으로 환산하는 방법으로는 직관적 방법, 경험적 방법, 통계적 방법 등이 있다. 본 연구에서는 통계적 방법의 일환인 혼합군집분석 기법을 적용하여 첨두/비첨두/심야시간에 대한 지속시간과 집중률을 산정한다. 한국건설기술연구원이 제공하는 2009년 전국 24시간 수시교통량 자료를 이용하였으며, 차종별 특성을 살펴보기 위해 승용차, 트럭, 전차종 등으로 나누어 분석을 실시하였다. 분석결과의 검증을 위해 한국도로공사의 TCS 통행시간 자료를 이용하였다. 검증결과 본 연구결과가 타 연구에 비해 비첨두/심야 시간에는 오차율이 낮으며, 첨두시에는 통행거리가 멀어질수록 오차율이 높아지는 결과를 보였다. 본 연구결과는 임의성을 배제할 수 있으며, 첨두율 추정치에 대한 신뢰성 검증을 수행할 수 있어 보다 안정적인 방법론이라 평가할 수 있을 것이다. 본 연구의 결과가 향후 교통수요 분석의 신뢰성 향상에 일조할 수 있기를 기대한다.

• 한국전산구조공학회논문집
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• 제19권4호
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• pp.419-427
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• 2006

본 논문에서는, 동조액체감쇠기(이하 TLD)만을 실험적 부분구조로 이용하여 TLD가 설치된 건축구조물의 지진 응답 제어효과를 평가하기 위한 실시간 하이브리드 실험법을 제안하고 진동대 실험을 통해 실험적으로 규명한다. 제안된 실험법에서, TLD가 설치된 전체구조물은 상부의 TLD와 하부의 구조물 부분으로 각각 실험적 그리고 수치해석적 부분구조로 나누어진다. 이때 부분구조 사이의 경계면에서 작용하는 하중 또는, TLD에 의한 제어력은 진동대에 설치된 전단형 로드셀에 의해 계측되며 진동대는, 계측된 경계면에서의 제어력이 상부에 작용하고 또한 동시에 기초에 지진하중이 작용하는 수치해석적 부분구조로부터 계산된 응답으로, 상부에 설치된 TLD를 가진하게 된다. 제안된 실험법에 의한 결과와 TLD와 건물모델 모두를 제작하여 실험하는 기존의 방법에 의한 실험 결과들은 서로 잘 일치하며, 이로써 본 논문에서 제안된 실험법을 이용하여 TLD의 제어성능을 손쉽게 평가 할 수 있음을 알 수 있다.

• International Journal of Control, Automation, and Systems
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• 제1권3호
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• pp.321-331
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• 2003

Experimental software datasets describing software projects in terms of their complexity and development time have been the subject of intensive modeling. A number of various modeling methodologies and modeling designs have been proposed including such approaches as neural networks, fuzzy, and fuzzy neural network models. In this study, we introduce the concept of the Rule-based fuzzy polynomial neural networks (RFPNN) as a hybrid modeling architecture and discuss its comprehensive design methodology. The development of the RFPNN dwells on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The architecture of the RFPNN results from a synergistic usage of RFNN and PNN. RFNN contribute to the formation of the premise part of the rule-based structure of the RFPNN. The consequence part of the RFPNN is designed using PNN. We discuss two kinds of RFPNN architectures and propose a comprehensive learning algorithm. In particular, it is shown that this network exhibits a dynamic structure. The experimental results include well-known software data such as the NASA dataset concerning software cost estimation and the one describing software modules of the Medical Imaging System (MIS).

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2005년도 춘계 학술발표회 논문집
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• pp.663-671
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• 2005

Distributed operation of overall structural design process, by which product and process optimization are implemented, is presented in this paper. The database-interconnected multilevel hybrid method, in which the conventional design method and the optimal design approach are combined, is utilized there. The method selectively takes the accustomed procedure of the conventional method in the conceptional framework of the optimal design. Design conditions are divided into primary and secondary criteria This staged application of design conditions reduces the computational burden for large complex optimization problems. Two kinds of numeric and graphic processes, are simultaneously implemented on the basis of concurrent engineering concepts in the distributed environment of PC networks. Numerical computation on server and graphic works on independent client are communicated through message passing. Numerical design is based on the optimization methodology and the drawing process is carried out by AutoCAD using the AutoLISP programming language. The prototype design experimentation for some steel trusses shows the validity and usability of the method. This study has sufficient adaptability and expandability in methodology, in that it is based on general theory and industry standard systems.