• 제목/요약/키워드: Input modeling

검색결과 1,775건 처리시간 0.033초

다결정 실리콘 박막 트랜지스터에서 공정 파라미터에 따른 전기적 특성의 모델링 (Modeling of Electrical Characteristics in Poly Silicon Thin Film Transistor with Process Parameter)

  • 정은식;최영식;이용재
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 2001년도 추계학술대회 논문집 Vol.14 No.1
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    • pp.201-204
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    • 2001
  • In this paper, for modeling of electrical characteristics in Poly Silicon Thin Film Transistors with process parameters set up optimum values, So, the I-V characteristics of poly silicon TFT parameters are examined and simulated in terms of the variations in process parameter. And these results compared and analyzed simulation values with examination value. The simulation program for characteristic analysis used SUPREM IV for processing, Matlab for modeling by mathematics, and SPICE for electric characteristic of devices. Input parameter for simulation characteristics is like condition of device process sequence, these electric characteristic of $I_D-V_D$ $I_D-V_G$, variations of grain size. The Gate oxide thickness of poly silicon are showed similar results between real device characteristics and simulation characteristics.

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차체 판넬의 가공 제작을 위한 금형형상의 효율적 모델링 (Efficient modeling of die-face shapes for stamping automobile outer panels)

  • 박종천;이건우;전기찬
    • 오토저널
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    • 제15권3호
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    • pp.96-110
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    • 1993
  • A procedure has been developed so that a die-face for stamping automobile outer panels can be design and modelled efficiently. The procedure is composed of four parts each of which corresponds to modeling major components of a die-face, i.e. tipped product, blankholder, draw beads, and step draw. The modeling techniques developed specifically for die-face design enable a designer to generate the shape of a die-face quickly with the minimum input, and the resulting models can be used in FEM analysis and NC tool path generation. This will lead to the reductions in lead time and manhours required for the design and manufacture of the stamping dies.

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3차원 공간자료 모델링 소프트웨어 개발 (3-D Spatial Data Modeling Software)

  • 이두성;김현규
    • 지구물리와물리탐사
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    • 제5권1호
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    • pp.1-5
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    • 2002
  • 본 연구에서는 2차원적으로 획득된 3차원 자료를 데이타베이스 화하고 이를 3차원적으로 분석하는데 필요한 도구인 모델링 및 시각화 소프트웨어를 ArcView환경에서 개발하였다. 본 소프트웨어는 유한개의 수평 단면으로 입력되는 자료로부터 개체의 형태를 3차원 공간상에서 구성하고 시각화한다. 프로그램은 구성된 개체로부터 임의 방향과 경사를 가진 단면을 생성할 수 있으며 단면의 수정을 통하여 해석자가 원하는 형태로 모델을 개선하는 기능을 보유하고 있다.

Generic Modeling System 개발 및 응용사례 (Generic Modeling System)

  • 조유정;임기수;나재일;이장열
    • 한국CDE학회지
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    • 제3권3호
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    • pp.36-45
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    • 1997
  • This paper presents the research on the development of Generic modeling system as a 3D CAD customizing system for the elevator design. This system enables to create a generic model which gives birth to many models. The generic model is expressed as a non-scale model or a standard model in this paper. Using the parametric design techniques, all their relationships are explicitly represented in the tables, not represented in implicit embedded coding. Owing to this method, designers can easily extend the generic model to contain more model families. All parametric relations are stored in relational database. A designer can retrieve various models from a generic model automatically, by using some key input values.

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An Efficient Virtual Teeth Modeling for Dental Training System

  • Kim, Lae-Hyun;Park, Se-Hyung
    • International Journal of CAD/CAM
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    • 제8권1호
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    • pp.41-44
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    • 2009
  • This paper describes an implementation of virtual teeth modeling for a haptic dental simulation. The system allows dental students to practice dental procedures with realistic tactual feelings. The system requires fast and stable haptic rendering and volume modeling techniques working on the virtual tooth. In our implementation, a volumetric implicit surface is used for intuitive shape modification without topological constraints and haptic rendering. The volumetric implicit surface is generated from input geometric model by using a closest point transformation algorithm. And for visual rendering, we apply an adaptive polygonization method to convert volumetric teeth model to geometric model. We improve our previous system using new octree design to save memory requirement while increase the performance and visual quality.

Statistical Modeling of Pretilt Angle Control using Ion-beam Alignment on Nitrogen Doped Diamond-like Carbon Thin Film

  • Kang, Hee-Jin;Lee, Jung-Hwan;Han, Jung-Min;Yun, Il-Gu;Seo, Dae-Shik
    • Transactions on Electrical and Electronic Materials
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    • 제7권6호
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    • pp.297-300
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    • 2006
  • The response surface modeling of the pretilt angle control using ion-beam (IB) alignment on nitrogen doped diamond-like carbon (NDLC) thin film layer is investigated. This modeling is used to analyze the variation of the pretilt angle under various process conditions. IB exposure angle and IB exposure time are considered as input factors. The analysis of variance technique is settled to analyze the statistical significance, and effect plots are also investigated to examine the relationships between the process parameters and the response. The model can allow us to reliably predict the pretilt angle with respect to the varying process conditions.

mGA를 사용한 복잡한 비선형 시스템의 뉴로-퍼지 모델링 (Neuro-Fuzzy Modeling of Complex Nonlinear System Using a mGA)

  • 최종일;이연우;주영훈;박진배
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 하계학술대회 논문집 D
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    • pp.2305-2307
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    • 2000
  • In this paper we propose a Neuro-Fuzzy modeling method using mGA for complex nonlinear system. mGA has more effective and adaptive structure than sGA with respect to using the changeable-length string. This paper suggest a new coding method for applying the model's input and output data to the number of optimul rules of fuzzy models and the structure and parameter identifications of membership function simultaneously. The proposed method realize optimal fuzzy inference system using the learning ability of Neural network. For fine-tune of the identified parameter by mGA, back-propagation algorithm used for optimulize the parameter of fuzzy set. The proposed fuzzy modeling method is applied to a nonlinear system to prove the superiority of the proposed approach through compare with ANFIS.

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Control system modeling of stock management for civil infrastructure

  • Abe, Masato
    • Smart Structures and Systems
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    • 제15권3호
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    • pp.609-625
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    • 2015
  • Management of infrastructure stock is essential in sustainability of society, and its analysis and optimization are studied in the light of control system modeling in this paper. At the first part of the paper, cost of stock management is analyzed based on macroscopic statistics on infrastructure stock and economical growth. Stock management burden relative to economy is observed to become larger at low economic growth periods in developed economies. Then, control system modeling of stock management is introduced and by augmenting maintenance actions as control input, dynamic behavior of stock is simulated and compared with existing time history statistics. Assuming steady state conditions, applicability of the model to cross sectional data is also demonstrated. The proposed model is enhanced so that both preventive and corrective maintenance can be included as system inputs, i.e., feedforward and feedback control inputs. Optimal management strategy to achieve specified deteriorated stock level with minimal cost, expressed in terms of preventive and corrective maintenance actions, is derived based on estimated parameter values for corrosion of steel bridges. Relative cost effectiveness of preventive maintenance is shown when target deteriorated stock level is lower.

다차원 평면 클러스터를 이용한 자기 구성 퍼지 모델링 (Self-Organizing Fuzzy Modeling Based on Hyperplane-Shaped Clusters)

  • 고택범
    • 제어로봇시스템학회논문지
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    • 제7권12호
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    • pp.985-992
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    • 2001
  • This paper proposes a self-organizing fuzzy modeling(SOFUM)which an create a new hyperplane shaped cluster and adjust parameters of the fuzzy model in repetition. The suggested algorithm SOFUM is composed of four steps: coarse tuning. fine tuning cluster creation and optimization of learning rates. In the coarse tuning fuzzy C-regression model(FCRM) clustering and weighted recursive least squared (WRLS) algorithm are used and in the fine tuning gradient descent algorithm is used to adjust parameters of the fuzzy model precisely. In the cluster creation, a new hyperplane shaped cluster is created by applying multiple regression to input/output data with relatively large fuzzy entropy based on parameter tunings of fuzzy model. And learning rates are optimized by utilizing meiosis-genetic algorithm in the optimization of learning rates To check the effectiveness of the suggested algorithm two examples are examined and the performance of the identified fuzzy model is demonstrated via computer simulation.

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퍼지 GMDH 모델과 하수처리공정에의 응용 (Fuzzy GMDH Model and Its Application to the Sewage Treatment Process)

  • 노석범;오성권;황형수;박희순
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1995년도 추계학술대회 학술발표 논문집
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    • pp.153-158
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    • 1995
  • In this paper, A new design method of fuzzy modeling is presented for the model identification of nonlinear complex systems. The proposed fuzzy GMDH modeling implements system structure and parameter identification using GMDH(Group Method of Data Handling) algorithm and linguistic fuzzy implication rules from input and output data of processes. In order to identify premise structure and parameter of fuzzy implication rules, GMDH algorithm and fuzzy reasoning method are used and the least square method is utilized for the identification of optimum consequence parameters. Time series data for gas furnaceare those for sewage treatment process are used for the purpose of evaluating the performance of the proposed fuzzy GMDH modeling. The results show that the proposed method can produce the fuzzy model with higher accuracy than other works achieved previously.

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