• Journal of Magnetics
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• 제19권4호
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• pp.315-322
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• 2014

In this work, Artificial Neural Network (ANN) was used to model the dynamic behavior of ferromagnetic hysteresis derived from performing the mean-field analysis on the Ising model. The effect of field parameters and system structure (via coordination number) on dynamic critical points was elucidated. The Ising magnetization equation was drawn from mean-field picture where the steady hysteresis loops were extracted, and series of the dynamic critical points for constructing dynamic phase-diagram were depicted. From the dynamic critical points, the field parameters and the coordination number were treated as inputs whereas the dynamic critical temperature was considered as the output of the ANN. The input-output datasets were divided into training, validating and testing datasets. The number of neurons in hidden layer was varied in structuring ANN network with highest accuracy. The network was then used to predict dynamic critical points of the untrained input. The predicted and the targeted outputs were found to match well over an extensive range even for systems with different structures and field parameters. This therefore confirms the ANN capabilities and indicates the ANN ability in modeling the ferromagnetic dynamic hysteresis behavior for establishing the dynamic-phase-diagram.

• 대한교통학회지
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• 제27권6호
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• pp.129-137
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• 2009

첨단교통체계의 기술발전과 교통 분석의 수준이 상세해짐에 따라 동적 교통 분석에 대한 필요성이 증가하고 있다. 기존의 정적인 분석이 하루 평균 개념의 통행특성과 네트워크 상태를 묘사한 반면, 동적 분석에서는 시간흐름에 따른 네트워크의 상태를 분석한다. 본 논문에서는 교통시스템 동적 분석의 필요성을 인식하여, 고속도로망을 대상으로 FTMS 자료를 활용한 분석 방법론을 개발하였다. 개별 차량의 실제 통행기록 자료인 TCS 자료를 이용하여 전국 고속도로망을 대상으로 동적 기종점 통행량을 구축하였으며, 시뮬레이션 연산시간 문제 해결을 위해 분석범위를 설정한 Subarea 분석을 활용하였다. 이를 위해 전국 고속도로망을 대상으로 구축된 시간대별 기종점 통행량을 Subarea 기종점 통행량으로 전환하기 위한 방법론을 개발하였다. 구축된 모형의 적용을 위해 시나리오 분석을 실시하였으며, 이를 통해 각각의 시나리오에 대하여 기존의 단편적인 효과분석과 달리 하루 중 시간대별 교통여건에 따른 네트워크 상태분석을 수행하였다. 본 연구는 동적 교통 분석의 초기 시도라는 점과 실제 기종점 자료인 FTMS 자료를 활용한 분석이라는 점에서 의미를 가지며, 현재 교통 분석의 큰 흐름인 동적 교통 분석의 필요성을 부각시키고자 한다. 향후 고속도로뿐만이 아닌 기타 도로를 포함한 모형 구축이 필요하며, Hybrid 모형 및 프로그램 개발을 통해 궁극적인 목표인 실시간동적 분석 모형 개발을 위한 연산시간 문제 해결이 필요할 것이다.

• 한국생물물리학회:학술대회논문집
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• 한국생물물리학회 2003년도 정기총회 및 학술발표회
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• pp.77-77
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• 2003

Gene expression in a cell is regulated by mutual activations or repressions between genes. Identifying the gene regulation network will be one of the most important research topics in the post genomic era. We propose a linear dynamic model of gene regulation for the yeast cell cycle. A small gene network consisting of about 40 genes is reconstructed from the analysis of micro-array gene expression data of yeast S. cerevisiae published by P. Spellman et al. We show that the network construction is consistent with the result of the hierarchical cluster analysis.

• Nuclear Engineering and Technology
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• 제40권5호
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• pp.375-386
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• 2008

Conventional static reliability analysis methods are inadequate for modeling dynamic interactions between components of a system. Various techniques such as dynamic fault tree, dynamic Bayesian networks, and dynamic reliability block diagrams have been proposed for modeling dynamic systems based on improvement of the conventional modeling methods. In this paper, we review these methods briefly and introduce dynamic nodes to the existing reliability graph with general gates (RGGG) as an intuitive modeling method to model dynamic systems. For a quantitative analysis, we use a discrete-time method to convert an RGGG to an equivalent Bayesian network and develop a software tool for generation of probability tables.

• 소성∙가공
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• 제31권2호
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• pp.81-88
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• 2022

Numerical analysis and dynamic material properties are required to analyze the behavior of workpiece during an electrohydraulic forming (EHF) process. In this study, EHF experiments were conducted under three conditions (6, 7, 8 kV). Dynamic material properties of Al 5052-H34 were inversely estimated through an ANN (Artificial Neural Network) model constructed based on LS-Dyna analysis results. Parameters of Cowper-Symonds constitutive equation, C and p, were used to implement dynamic material properties. By comparing experimental results of three conditions with ANN model results, optimized parameters were obtained. To determine the reliability of the derived parameters, experimental results, LS-Dyna analysis results, and ANN results of three conditions were compared using MSE and SMAPE. Valid parameters were obtained because values of indicators were within confidence intervals.

• The Journal of Asian Finance, Economics and Business
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• 제8권9호
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• pp.113-119
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• 2021

With the increasing pressure of international competition, urban agglomeration cooperation and innovation had become an important means of regional economic development. This study analyzed the spatial characteristics of the Urban Cooperative Innovation Network in Guangdong-Hong Kong-Macao Greater Bay Area, found out the dynamic evolution law of innovation, provided suggestions for policy management departments, and effectively planned the industrial layout. According to the data of the State Intellectual Property Office of China, this study researched invention patents from 2005 to 2019. This paper constructed the urban cooperative innovation network, and took 11 cities in the bay area as the research objects, and used social network analysis to study the spatial structure and dynamic evolution of the urban innovation network. Every indicator reflected the urban cooperative innovation, but they all showed a certain decline in 2008-2010. And it is inferred that the innovation network space of each city will be "obvious fist advantages, significant spillover effect and weakening role of Hong Kong and Macao". This paper divided urban cooperative innovation of Guangdong-Hong Kong-Macao Greater Bay Area into three stages. Summing up the characteristics of each stage is helpful to recognize the changes of urban cooperative innovation and to do a good job in industrial layout planning.

• Nuclear Engineering and Technology
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• 제54권4호
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• pp.1213-1220
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• 2022

The Emergency Diesel Generator (EDG) is a critical and essential part of the Nuclear Power Plant (NPP). Due to past catastrophic disasters, critical systems of NPP like EDG are designed to meet high dependability requirements. Therefore, we propose a framework for the dynamic reliability assessment using the Fault Tree and the Dynamic Bayesian Network. In this framework, the information of the component's failure probability is updated based on observed data. The framework is powerful to perform qualitative as well as quantitative analysis of the system. The validity of the framework is done by applying it on several NPP systems.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제3B권3호
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• pp.122-127
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• 2003

This paper presents a new time-stepping 3-D analysis method coupled with an external circuit with motion equation for dynamic transient analysis of induction machines. In this method, the magneto-motive force (MMF) generated by induced current is modeled as a passive source in the magnetic equivalent network. So, by using only scalar potential at each node, the method is able to analyze induction machines with faster computation time and less memory requirement than conventional numerical methods. Also, this method is capable of modeling the movement of the mover without the need for re-meshing and analyzing the time harmonics for dynamic characteristics. From comparisons between the results of the analysis and the experiments, it is verified that the proposed method is capable of estimating the torque, harmonic field, etc. as a function of time with superior accuracy.

• 한국경영과학회지
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• 제40권1호
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• pp.5-19
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• 2015

Literatures on open innovation have two major limitations. First, either on a firm level or on an industry level did they analyze the open innovation issues. The results of a firm's innovation can be diffused through the whole network and the firm can learn back from the network knowledge. Prior literatures did not consider the feedback loop among firms and network in which the firms are involved. Second, most open innovation research had a static perspective on firm's innovation performance. Since the diffusion, spill-over and learning among network members are involved over time, the open innovation is intrinsically dynamic. From the dynamic perspective, we can appreciate the fundamental attributes of the open innovation network which involves diverse firms, research institutes, and universities. In order to overcome the limitations, we suggest a dynamic model for open innovation network. We build an agent-based model which consists of heterogeneous firms. The firms are connected through a scale-free network which is formed by preferential attachment. Through the diverse scenario of simulation, we collect massive data on the firm level and analyze them both on firm and industry level. From the analysis, we found that, on industry level, the overall performance of open innovation increases as the internal research capability, absorptive capacity, and learning curve coefficient increase. Noticeably, as the deprecation rate of knowledge increases, the variability of knowledge increases. From the firm level analysis, we found that the industry-level variables had a significant effect on the firm's innovation performance lasting through all the time, whereas the firm-level variables had only on the early phase of innovation.

• Journal of Mechanical Science and Technology
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• 제19권spc1호
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• pp.255-264
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• 2005

In this paper, a practical bushing model is proposed to improve the accuracy of the vehicle dynamic analysis. The results of the rubber bushing are used to develop an empirical bushing model with an artificial neural network. A back propagation algorithm is used to obtain the weighting factor of the neural network. Since the output for a dynamic system depends on the histories of inputs and outputs, Narendra algorithm of 'NARMAX' form is employed to consider these effects. A numerical example is carried out to verify the developed bushing model. Then, a full car dynamic model with artificial neural network bushings is simulated to show the feasibility of the proposed bushing model.