• Title, Summary, Keyword: Analysis Model

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Analysis of Hydraulic Characteristics in the Middle Reaches of Nak-Dong River using 2-Dimensional Numerical Analyis Model (2차원 수치해석모형을 이용한 낙동강 중류구간의 하천흐름 해석)

  • Han, Sung-Dea;Choi, Hyun;Ahn, Chang-Hwan;Lee, Je-Yun
    • Proceedings of the Korea Water Resources Association Conference
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    • pp.1732-1736
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    • 2008
  • The characteristics of a river flow analysis are significant for river maintenance plan. At the present time, HEC-RAS, 1-Dimensional Numerical Analysis Model, is mainly applied to analyze the character of a river flow. The shape of a river is somewhat in longitudinal linear form. It was suspected that the usage of 1-dimensional numerical analysis model is more economical. Development of numerical analysis models and computers are possible to calculate large volume. Hence, it is possible to adapt the analysis of the key stations by 2-dimensional numerical analysis model. The limitation of 1-Dimensional Numerical Analysis Model is that it is hard to evaluate structure affection of numerical simulation by energy loss coefficient at river structure analyzing. When adaptation of the 2-dimensional numerical analysis model in river structure ensues, it takes more objective analyzing than 1-dimensional numerical analysis model for flow affection by river structure. 2-dimensional numerical analysis model consults with the different structure position of hydraulic characteristics and different water depth of shape and scope in vertical flow. 1-dimensional numerical analysis model is possible to simulate with only energy loss coefficient for sudden river section changing, sudden waterway changing by curved. 2-dimensional numerical analysis model use original geographical features. So the model removes technical subjectivity of faulty judgment. It is an objective analysis.

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Sensitivity and Uncertainty Analysis of Two-Compartment Model for the Indoor Radon Pollution (실내 라돈오염 해석을 위한 2구역 모델의 민감도 및 불확실성 분석)

  • 유동한;이한수;김상준;양지원
    • Journal of Korean Society for Atmospheric Environment
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    • v.18 no.4
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    • pp.327-334
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    • 2002
  • The work presents sensitivity and uncertainty analysis of 2-compartment model for the evaluation of indoor radon pollution in a house. Effort on the development of such model is directed towards the prediction of the generation and transfer of radon in indoor air released from groundwater. The model is used to estimate a quantitative daily human exposure through inhalation of such radon based on exposure scenarios. However, prediction from the model has uncertainty propagated from uncertainties in model parameters. In order to assess how model predictions are affected by the uncertainties of model inputs, the study performs a quantitative uncertainty analysis in conjunction with the developed model. An importance analysis is performed to rank input parameters with respect to their contribution to model prediction based on the uncertainty analysis. The results obtained from this study would be used to the evaluation of human risk by inhalation associated with the indoor pollution by radon released from groundwater.

A Study on Corps / Division Operation Analysis Using Simplified Corps Level Wargame Model (군단급 간이분석 워게임모형을 이용한 군단 및 사단 작전분석 방안 연구)

  • 박승환;강성진
    • Journal of the military operations research society of Korea
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    • v.24 no.2
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    • pp.95-116
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    • 1998
  • Many different kinds of wargame models have been developed and used in training and analysis purpose. However, there has been few wargame model which analyze corps or division level operational analysis. Recently KIDA develops corps level operational analysis model based on START(simplified tool for analysis of regional treats) model developed by RAND. This model runs in a PC level with 2MB memory and provides one day combat results within 30 seconds. Only one or three person can operate this model and evaluate multiple corps level operational analysis including chemical effects, $C^3I$ capacity, new weapon system effectiveness and other qualitative effects. We tested this model and evaluated input and output data. We showed that this model can be applied in division level operational analysis also. As an example division level application procedure and sensitivity analysis data was provided. We also find some limitation and problems in the model and suggest application areas and improving methods.

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A Comparison of Barton-Bandis Joint Model and Mohr-Coulomb Joint Model for Tunnel Stability Analysis with DEM (개별요소법을 이용한 터널 안정성 해석에 있어 Barton-Bandis 절리 모델과 Mohr-Coulomb절리 모델의 비교)

  • 이성규;김치환
    • Tunnel and Underground Space
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    • v.11 no.2
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    • pp.167-173
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    • 2001
  • The joint model has influence on the results of discontinuum analysis. In this study the results of discontinuum analysis with Barton-Bandis joint model(BB model) and with Mohr-Coulomb joint model(MC model) are compared. The results of continuum analysis under the same condition are compared with the results of discontinuum analysis to investigate the behavior of rockmass around tunnel. The result of continuum analysis and that of discontinuum analysis with BB model show similar distribution of displacement and stress. On the other hand, the discontinuum analysis with MC model shows different displacement distribution and stress distribution. Moreover, the displacement and minor principal stress of the discontinuum analysis with MC model are smaller than those of continuum analysis, although the joints are explicitly considered in the discontinuum analysis. These results are originated from the limitation of MC model in simulating joint deformation behavior, especially the assumption of constant dilation jingle independent of it)int 7hear displacement.

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Sentiment Analysis Using Deep Learning Model based on Phoneme-level Korean (한글 음소 단위 딥러닝 모형을 이용한 감성분석)

  • Lee, Jae Jun;Kwon, Suhn Beom;Ahn, Sung Mahn
    • Journal of Information Technology Services
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    • v.17 no.1
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    • pp.79-89
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    • 2018
  • Sentiment analysis is a technique of text mining that extracts feelings of the person who wrote the sentence like movie review. The preliminary researches of sentiment analysis identify sentiments by using the dictionary which contains negative and positive words collected in advance. As researches on deep learning are actively carried out, sentiment analysis using deep learning model with morpheme or word unit has been done. However, this model has disadvantages in that the word dictionary varies according to the domain and the number of morphemes or words gets relatively larger than that of phonemes. Therefore, the size of the dictionary becomes large and the complexity of the model increases accordingly. We construct a sentiment analysis model using recurrent neural network by dividing input data into phoneme-level which is smaller than morpheme-level. To verify the performance, we use 30,000 movie reviews from the Korean biggest portal, Naver. Morpheme-level sentiment analysis model is also implemented and compared. As a result, the phoneme-level sentiment analysis model is superior to that of the morpheme-level, and in particular, the phoneme-level model using LSTM performs better than that of using GRU model. It is expected that Korean text processing based on a phoneme-level model can be applied to various text mining and language models.

Flutter Analysis of Small Aircraft using Full Airframe Dynamic FE Model (전기체 동적 유한요소 모델을 이용한 소형항공기 플러터 해석)

  • Lee, Sang-Wook;Paek, Seung-Kil;Kim, Sung-Chan;Hwang, In-Hee
    • Proceedings of the KSME Conference
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    • pp.424-429
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    • 2008
  • Aircraft flutter analysis model consists of dynamic FE model and aerodynamic model. Dynamic FE model is composed of stiffness and mass model, and is used for the prediction of normal mode characteristics of the structure. Since aircraft flutter analysis is normally performed in the modal domain, dynamic FE model shall be constructed to describe the modal characteristics of the structure with sufficient accuracy. In this study, dynamic FE modeling method was described using full airframe FE model and structural and system weight data for aircraft flutter analysis. In addition, full airframe dynamic FE model for composite small aircraft was constituted for normal mode and flutter analysis, and the mass modeling results were compared with the target weight data to validate the mass modeling method proposed. Finally, full airframe flutter analysis of composite small aircraft was performed with the dynamic FE model and the aerodynamic model composed.

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Applicability of Beam Model among Earthquake Response Analysis Models of Liquid-Storage Tank (액체저장탱크의 지진응답해석 모델 중 빔 모델의 적용성)

  • Jin, Byeong-Moo;Jeon, Se-Jin;Kim, Young-Jin
    • Proceedings of the Korea Concrete Institute Conference
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    • pp.696-699
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    • 2004
  • Generally, the time history analysis among seismic response analyses of a structure needs more times than static analysis. Therefore the mechanical model of a structure has been used as a simple lumped parameter model in time history analysis. For the most cases, the simple mechanical model shows the similar results to that of detailed finite element model. so it is reasonable to use the simple mode] in preliminary analysis. In seismic design of liquid storage tank, such as LNG storage tank, the lumped parameter mode] also is being used in preliminary analysis, however sometimes shows the differences to the results of detailed finite element model. Therefore in this study, the dynamic characteristics between lumped parameter model and detailed finite model is compared for the variables such as height/diameter of liquid-storage tank and thickness of wall, then the applicability of beam mode] to the seismic response analysis are evaluated for some liquid storage tanks.

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A Study on Behavioral Model and Spatial Configuration Analysis model in the Architectural Space (건축공간의 행동모델과 공간구조 분석모델에 관한 연구)

  • Lee, Jong-Ruyl
    • Journal of The Korean Digital Architecture Interior Association
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    • v.12 no.2
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    • pp.61-66
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    • 2012
  • In space syntax, the mathmatical process to get a integration could be restrictive in understanding spatial configuration since it is based on only one behavior model. In this study, As another approach to spatial configuration analysis based on behavioral model, there is the simulation tracking analysis model that simulates the movements of human in the space and analyze them. In this study, the relationship between integration and behavioral model will be defined and the similarities and the differences between space syntax and the simulation tracking analysis model will be demonstrated. Furthermore, these two analysis models will be understood as a variety of tools that can analyze an object in multiple viewpoints.

Regional Extension of the Neural Network Model for Storm Surge Prediction Using Cluster Analysis (군집분석을 이용한 국지해일모델 지역확장)

  • Lee, Da-Un;Seo, Jang-Won;Youn, Yong-Hoon
    • Atmosphere
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    • v.16 no.4
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    • pp.259-267
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    • 2006
  • In the present study, the neural network (NN) model with cluster analysis method was developed to predict storm surge in the whole Korean coastal regions with special focuses on the regional extension. The model used in this study is NN model for each cluster (CL-NN) with the cluster analysis. In order to find the optimal clustering of the stations, agglomerative method among hierarchical clustering methods was used. Various stations were clustered each other according to the centroid-linkage criterion and the cluster analysis should stop when the distances between merged groups exceed any criterion. Finally the CL-NN can be constructed for predicting storm surge in the cluster regions. To validate model results, predicted sea level value from CL-NN model was compared with that of conventional harmonic analysis (HA) and of the NN model in each region. The forecast values from NN and CL-NN models show more accuracy with observed data than that of HA. Especially the statistics analysis such as RMSE and correlation coefficient shows little differences between CL-NN and NN model results. These results show that cluster analysis and CL-NN model can be applied in the regional storm surge prediction and developed forecast system.

A Novel Data Prediction Model using Data Weights and Neural Network based on R for Meaning Analysis between Data (데이터간 의미 분석을 위한 R기반의 데이터 가중치 및 신경망기반의 데이터 예측 모형에 관한 연구)

  • Jung, Se Hoon;Kim, Jong Chan;Sim, Chun Bo
    • Journal of Korea Multimedia Society
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    • v.18 no.4
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    • pp.524-532
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    • 2015
  • All data created in BigData times is included potentially meaning and correlation in data. A variety of data during a day in all society sectors has become created and stored. Research areas in analysis and grasp meaning between data is proceeding briskly. Especially, accuracy of meaning prediction and data imbalance problem between data for analysis is part in course of something important in data analysis field. In this paper, we proposed data prediction model based on data weights and neural network using R for meaning analysis between data. Proposed data prediction model is composed of classification model and analysis model. Classification model is working as weights application of normal distribution and optimum independent variable selection of multiple regression analysis. Analysis model role is increased prediction accuracy of output variable through neural network. Performance evaluation result, we were confirmed superiority of prediction model so that performance of result prediction through primitive data was measured 87.475% by proposed data prediction model.