• Title/Summary/Keyword: 입력변수선택

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A Study on the Prediction of Turbidity near the Confluence of Banbyeoncheon by Using the KU-RLMS Model (KU-RLMS 모형을 이용한 반변천 합류부 탁도 예측에 관한 연구)

  • Lim, Ji-Hyun;Lee, Nam-Joo;Lyu, Si-Wan;Yeo, Hong-Koo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2007.05a
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    • pp.1214-1218
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    • 2007
  • 댐 하류로 탁수를 선택적으로 배제하기 위해서는 방류 탁수가 하류에 미치는 영향을 정확히 예측할 수 있는 하천 탁도 예측 및 관리시스템 구축이 필요하다. 낙동강과 반변천의 합류부에서의 이차원적인 혼합에 관한 수치해석 결과는 완전혼합을 가정하는 일차원 수질모델링의 초기 입력자료에 사용됨으로써 낙동강 본류 전체구간의 탁도 모의결과의 정확성을 높이는 데 사용될 수 있다. 본 연구는 낙동강의 중상류에 위치한 반변천 합류부에 평면 이차원 비정상 수치모형인 KU-RLMS 모형을 적용하여 탁도 변화 특성을 규명할 목적으로 수행하였다. KU-RLMS 모형은 하천 및 저수지의 국부적인 수리, 수질, 유사이동 해석을 위해 개발된 평면 이차원 비정상 수치모형이다. 직사각형 격자를 사용하는 유한차분법의 단점을 보완하기 위해, 수심적분된 2차원 연속방정식, 운동량방정식, 이송확산방정식을 불규칙한 경계를 현실적으로 모사할 수 있는 직교곡선 좌표계로 변환한 방정식을 사용한다. 이 모형은 흐름, 농도, 지형변화를 조합하여 계산할 수 있는 모형으로서 점착성 및 비점착성 유사의 이동을 모의할 수 있다. 수치모형 적용을 위한 현황분석으로 안동 및 임하 조정지댐의 방류량, 안동 수위관측소의 수위, 법흥교 및 포진교 지점의 탁도 자료를 분석하였다. 이송확산모형의 보정을 위해, 안동대교 지점의 탁도 횡분포 측정 자료를 사용하여 확산계수에 대한 매개변수 추정 및 검증을 수행하였다. 또한, 안동조정지댐과 임하조정지댐의 방류량 및 방류탁도을 고려하여 수치모의조건을 결정하였으며, 각 조건에 대한 탁도 변화 특성을 분석하였다.된 주변국이 될 수밖에 없을 것이다. 21세기 문화산업에서 우리가 판단하게 될 디자인의 가치는 계몽의 원리에 대한 '역사성'과 '현재성'의 변증법에 달려있는 것이며, 새로운 철학, 새로운 문명, 새로운 세계를 열어가는 것이다.r$ (地理志)에는 추현리와 이미 외리를 언급하면서 상주의 자기제작의 위상을 짐작하는 기록이 언급되면서 전국의 상품의 절반을 담당하고 있었음을 알 수 있었다. $\ulcorner$경상도지리지$\lrcorner$(慶尙道地理志)에는 상주가 8곳으로 1/3의 자기 생산을 담당하고 있었다. $\ulcorner$경상도지리지$\lrcorner$(慶尙道地理志)에는 $\ulcorner$세종실록$\lrcorner$(世宗實錄) $\ulcorner$지리지$\lrcorner$(地理志)와 동년대에 동일한 목적으로 찬술되었음을 알 수 있다. $\ulcorner$경상도실록지리지$\lrcorner$(慶尙道實錄地理志)에는 $\ulcorner$세종실록$\lrcorner$(世宗實錄) $\ulcorner$지리지$\lrcorner$(地理志)와의 비교를 해보면 상 중 하품의 통합 9개소가 삭제되어 있고, $\ulcorner$동국여지승람$\lrcorner$(東國與地勝覽) 에서는 자기소와 도기

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An Efficient CPLD Technology Mapping considering Area under Time Constraint (시간 제약 조건하에서 면적을 고려한 효율적인 CPLD 기술 매핑)

  • Kim, Jae-Jin;Kim, Hui-Seok
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.38 no.1
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    • pp.79-85
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    • 2001
  • In this paper, we propose a new technology mapping algorithm for CPLD consider area under time constraint(TMFCPLD). This technology mapping algorithm detect feedbacks from boolean networks, then variables that have feedback are replaced to temporary variables. Creating the temporary variables transform sequential circuit to combinational circuit. The transformed circuits are represented to DAG. After traversing all nodes in DAG, the nodes that have output edges more than two are replicated and reconstructed to fanout free tree. This method is for reason to reduce area and improve total run time of circuits by TEMPLA proposed previously. Using time constraints and delay time of device, the number of graph partitionable multi-level is decided. Initial cost of each node are the number of OR-terms that it have. Among mappable clusters, clusters of which the number of multi-level is least is selected, and the graph is partitioned. Several nodes in partitioned clusters are merged by collapsing, and are fitted to the number of OR-terms in a given CLB by bin packing. Proposed algorithm have been applied to MCNC logic synthesis benchmark circuits, and have reduced the number of CLBs by 62.2% than those of DDMAP. And reduced the number of CLBs by 17.6% than those of TEMPLA, and reduced the number of CLBs by 4.7% than those of TMCPLD. This results will give much efficiency to technology mapping for CPLDs.

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Development of Hybrid Vision Correction Algorithm (Hybrid Vision Correction Algorithm의 개발)

  • Ryu, Yong Min;Lee, Eui Hoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.1
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    • pp.61-73
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    • 2021
  • Metaheuristic search methods have been developed to solve problems with a range of purpose functions in situations lacking information and time constraints. In this study, the Hybrid Vision Correction Algorithm (HVCA), which enhances the performance of the Vision Correction Algorithm (VCA), was developed. The HVCA has applied two methods to improve the performance of VCA. The first method changes the parameters required by the user for self-adaptive parameters. The second method, the CGS structure of the Exponential Bandwidth Harmony Search With a Centralized Global Search (EBHS-CGS), was added to the HVCA. The HVCA consists of two structures: CGS and VCA. To use the two structures, a method was applied to increase the probability of selecting the structure with the optimal value as it was performed. The optimization problem was applied to determine the performance of the HVCA, and the results were compared with Harmony Search (HS), Improved Harmony Search (IHS), and VCA. The HVCA improved the number of times to find the optimal value during 100 repetitions compared to HS, IHS, and VCA. Moreover, the HVCA reduced the Number of Function Evaluations (NFEs). Therefore, the performance of the HVCA has been improved.

A Study on the traffic flow prediction through Catboost algorithm (Catboost 알고리즘을 통한 교통흐름 예측에 관한 연구)

  • Cheon, Min Jong;Choi, Hye Jin;Park, Ji Woong;Choi, HaYoung;Lee, Dong Hee;Lee, Ook
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.3
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    • pp.58-64
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    • 2021
  • As the number of registered vehicles increases, traffic congestion will worsen worse, which may act as an inhibitory factor for urban social and economic development. Through accurate traffic flow prediction, various AI techniques have been used to prevent traffic congestion. This paper uses the data from a VDS (Vehicle Detection System) as input variables. This study predicted traffic flow in five levels (free flow, somewhat delayed, delayed, somewhat congested, and congested), rather than predicting traffic flow in two levels (free flow and congested). The Catboost model, which is a machine-learning algorithm, was used in this study. This model predicts traffic flow in five levels and compares and analyzes the accuracy of the prediction with other algorithms. In addition, the preprocessed model that went through RandomizedSerachCv and One-Hot Encoding was compared with the naive one. As a result, the Catboost model without any hyper-parameter showed the highest accuracy of 93%. Overall, the Catboost model analyzes and predicts a large number of categorical traffic data better than any other machine learning and deep learning models, and the initial set parameters are optimized for Catboost.

A Study of Fatigue Damage Factor Evaluation for Railway Turnout Crossing using Qualitative Analysis & Field Test (현장측정 및 정성분석기법을 이용한 분기기 망간 크로싱의 피로손상도 평가에 관한 연구)

  • Park, Yong-Gul;Choi, Jung-Youl;Eum, Ki-Young
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.6D
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    • pp.881-893
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    • 2008
  • The major objective of this study is to investigate the fatigue damage factor evaluation of immovability crossing for railway turnout by the field test and qualitative analysis. From the field test results of the servicing turnout crossing and qualitative analysis with frictional wear which section stiffness decreased, it was evaluated fatigue life of servicing turnout crossing. Most design practices have not taken advantage of the advanced theories in the modern fracture mechanics and finite element analysis due to complexity of analysis as well as the large quantity of vaguely defined parameters in actual designs. This paper considers fatigue problems in turnout crossing using effective analytical and design tools from the field of qualitative constraint reasoning. A set of software modules was developed for fatigue analysis and evaluation, which is easily applicable in engineering practices of designers. The techniques enable the use complex analysis formulations to tackle practical problems with uncertainties, and present the design outcome in two-dimensional design space solution. Appropriate engineering assumptions and judgments in carrying out these procedures, often the most difficult part for practicing engineers, can be partially produced by using qualitative reasoning to define the trends and ranges, interval constraint analysis to derive the controlling parameters, as well as design space to account for practical experience.

Incremental Ensemble Learning for The Combination of Multiple Models of Locally Weighted Regression Using Genetic Algorithm (유전 알고리즘을 이용한 국소가중회귀의 다중모델 결합을 위한 점진적 앙상블 학습)

  • Kim, Sang Hun;Chung, Byung Hee;Lee, Gun Ho
    • KIPS Transactions on Software and Data Engineering
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    • v.7 no.9
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    • pp.351-360
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    • 2018
  • The LWR (Locally Weighted Regression) model, which is traditionally a lazy learning model, is designed to obtain the solution of the prediction according to the input variable, the query point, and it is a kind of the regression equation in the short interval obtained as a result of the learning that gives a higher weight value closer to the query point. We study on an incremental ensemble learning approach for LWR, a form of lazy learning and memory-based learning. The proposed incremental ensemble learning method of LWR is to sequentially generate and integrate LWR models over time using a genetic algorithm to obtain a solution of a specific query point. The weaknesses of existing LWR models are that multiple LWR models can be generated based on the indicator function and data sample selection, and the quality of the predictions can also vary depending on this model. However, no research has been conducted to solve the problem of selection or combination of multiple LWR models. In this study, after generating the initial LWR model according to the indicator function and the sample data set, we iterate evolution learning process to obtain the proper indicator function and assess the LWR models applied to the other sample data sets to overcome the data set bias. We adopt Eager learning method to generate and store LWR model gradually when data is generated for all sections. In order to obtain a prediction solution at a specific point in time, an LWR model is generated based on newly generated data within a predetermined interval and then combined with existing LWR models in a section using a genetic algorithm. The proposed method shows better results than the method of selecting multiple LWR models using the simple average method. The results of this study are compared with the predicted results using multiple regression analysis by applying the real data such as the amount of traffic per hour in a specific area and hourly sales of a resting place of the highway, etc.

Dynamic Behavior of Reactor Internals under Safe Shutdown Earthquake (안전정기지진하의 원자로내부구조물 거동분석)

  • 김일곤
    • Computational Structural Engineering
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    • v.7 no.3
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    • pp.95-103
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    • 1994
  • The safety related components in the nuclear power plant should be designed to withstand the seismic load. Among these components the integrity of reactor internals under earthquake load is important in stand points of safety and economics, because these are classified to Seismic Class I components. So far the modelling methods of reactor internals have been investigated by many authors. In this paper, the dynamic behaviour of reactor internals of Yong Gwang 1&2 nuclear power plants under SSE(Safe Shutdown Earthquake) load is analyzed by using of the simpled Global Beam Model. For this, as a first step, the characteristic analysis of reactor internal components are performed by using of the finite element code ANSYS. And the Global Beam Model for reactor internals which includes beam elements, nonlinear impact springs which have gaps in upper and lower positions, and hydrodynamical couplings which simulate the fluid-filled cylinders of reactor vessel and core barrel structures is established. And for the exciting external force the response spectrum which is applied to reactor support is converted to the time history input. With this excitation and the model the dynamic behaviour of reactor internals is obtained. As the results, the structural integrity of reactor internal components under seismic excitation is verified and the input for the detailed duel assembly series model could be obtained. And the simplicity and effectiveness of Global Beam Model and the economics of the explicit Runge-Kutta-Gills algorithm in impact problem of high frequency interface components are confirmed.

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A Development of Automatic Lineament Extraction Algorithm from Landsat TM images for Geological Applications (지질학적 활용을 위한 Landsat TM 자료의 자동화된 선구조 추출 알고리즘의 개발)

  • 원중선;김상완;민경덕;이영훈
    • Korean Journal of Remote Sensing
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    • v.14 no.2
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    • pp.175-195
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    • 1998
  • Automatic lineament extraction algorithms had been developed by various researches for geological purpose using remotely sensed data. However, most of them are designed for a certain topographic model, for instance rugged mountainous region or flat basin. Most of common topographic characteristic in Korea is a mountainous region along with alluvial plain, and consequently it is difficult to apply previous algorithms directly to this area. A new algorithm of automatic lineament extraction from remotely sensed images is developed in this study specifically for geological applications. An algorithm, named as DSTA(Dynamic Segment Tracing Algorithm), is developed to produce binary image composed of linear component and non-linear component. The proposed algorithm effectively reduces the look direction bias associated with sun's azimuth angle and the noise in the low contrast region by utilizing a dynamic sub window. This algorithm can successfully accomodate lineaments in the alluvial plain as well as mountainous region. Two additional algorithms for estimating the individual lineament vector, named as ALEHHT(Automatic Lineament Extraction by Hierarchical Hough Transform) and ALEGHT(Automatic Lineament Extraction by Generalized Hough Transform) which are merging operation steps through the Hierarchical Hough transform and Generalized Hough transform respectively, are also developed to generate geological lineaments. The merging operation proposed in this study is consisted of three parameters: the angle between two lines($\delta$$\beta$), the perpendicular distance($(d_ij)$), and the distance between midpoints of lines(dn). The test result of the developed algorithm using Landsat TM image demonstrates that lineaments in alluvial plain as well as in rugged mountain is extremely well extracted. Even the lineaments parallel to sun's azimuth angle are also well detected by this approach. Further study is, however, required to accommodate the effect of quantization interval(droh) parameter in ALEGHT for optimization.

Multiple Linear Analysis for Generating Parametric Images of Irreversible Radiotracer (비가역 방사성추적자 파라메터 영상을 위한 다중선형분석법)

  • Kim, Su-Jin;Lee, Jae-Sung;Lee, Won-Woo;Kim, Yu-Kyeong;Jang, Sung-June;Son, Kyu-Ri;Kim, Hyo-Cheol;Chung, Jin-Wook;Lee, Dong-Soo
    • Nuclear Medicine and Molecular Imaging
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    • v.41 no.4
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    • pp.317-325
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    • 2007
  • Purpose: Biological parameters can be quantified using dynamic PET data with compartment modeling and Nonlinear Least Square (NLS) estimation. However, the generation of parametric images using the NLS is not appropriate because of the initial value problem and excessive computation time. In irreversible model, Patlak graphical analysis (PGA) has been commonly used as an alternative to the NLS method. In PGA, however, the start time ($t^*$, time where linear phase starts) has to be determined. In this study, we suggest a new Multiple Linear Analysis for irreversible radiotracer (MLAIR) to estimate fluoride bone influx rate (Ki). Methods: $[^{18}F]Fluoride$ dynamic PET scans was acquired for 60 min in three normal mini-pigs. The plasma input curve was derived using blood sampling from the femoral artery. Tissue time-activity curves were measured by drawing region of interests (ROls) on the femur head, vertebra, and muscle. Parametric images of Ki were generated using MLAIR and PGA methods. Result: In ROI analysis, estimated Ki values using MLAIR and PGA method was slightly higher than those of NLS, but the results of MLAIR and PGA were equivalent. Patlak slopes (Ki) were changed with different $t^*$ in low uptake region. Compared with PGA, the quality of parametric image was considerably improved using new method. Conclusion: The results showed that the MLAIR was efficient and robust method for the generation of Ki parametric image from $[^{18}F]Fluoride$ PET. It will be also a good alternative to PGA for the radiotracers with irreversible three compartment model.

A Study on the Evaluation of Materials for Aircraft Turbofan Engine Using Data Base. (항공기용 터어보팬 엔진의 재료선정용 DATA BASE를 이용한 재료평가에 관한 연구)

  • Kim, Gwang-Bae;Bu, Jun-Hong;Kim, Hak-Bong;Im, Gyeong-Ho;Yu, Sang-Sin
    • Korean Journal of Materials Research
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    • v.1 no.3
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    • pp.156-167
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    • 1991
  • The purpose of this study is to develop a data base for material selection of turbofan engines, which is preferred in these days on many application due to their high performance with economical operation. Hundreds of Super Alloys have been developed by this time, each having special properties. Since it is very difficult task for a design engineer to select materials of adequate Properties for specific engine components, a good data bate is strongly desired to manage informations on various kinds of materials. However, no basic research is reported in this area so far in our country. The operating conditions such as temperature, pressure, rpm of spools are assumed to be provided by other mechanical studies. Creep rupture strength, corrosion resistance, yield strength, thermal expansion, melting point, etc., are considered as typical properties in this study to search a group of candidate materials. Formability, manufacturing or purchase cost can also be important variables to be considered. As a result of this study, a user-friendly computer program has been developed for input of new material information, interactive material selection, and output of selection results. Finally, discussion is presented from. the viewpoint of materials engineering. A method to evaluate the performance of the selected materials is also suggested.

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