• Title/Summary/Keyword: 확률 적합도 모델

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The Development of e-Learning System for Science and Engineering Mathematics using Computer Algebra System (컴퓨터 대수 시스템을 이용한 이공계 수학용이러닝 시스템 개발)

  • Park, Hong-Joon;Jun, Young-Cook;Jang, Moon-Suk
    • The KIPS Transactions:PartA
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    • v.14A no.6
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    • pp.383-390
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    • 2007
  • This paper describes the e-learning system for science and engineering mathematics using computer algebra system and Bayesian inference network. The best feature of this system is using one of the most recent mathematical dynamic web content authoring model which is called client independent dynamic web content authoring model and using the Bayesian inference network for diagnosing student's learning. The authoring module using computer algebra system provides teacher-user with easy way to make dynamic mathematical web contents. The diagnosis module using Bayesian inference network helps students know the weaker parts of their learning, in this way our system determines appropriate next learning sequences in order to provide supplementary learning feedback.

Development of the National Integrated Daily Weather Index (DWI) Model to Calculate Forest Fire Danger Rating in the Spring and Fall (봄철과 가을철의 기상에 의한 전국 통합 산불발생확률 모형 개발)

  • Won, Myoungsoo;Jang, Keunchang;Yoon, Sukhee
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.20 no.4
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    • pp.348-356
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    • 2018
  • Most of fires were human-caused fires in Korea, but meteorological factors are also big contributors to fire behavior and its spread. Thus, meteorological factors as well as topographical and forest factors were considered in the fire danger rating systems. This study aims to develop an advanced national integrated daily weather index(DWI) using weather data in the spring and fall to support forest fire prevention strategy in South Korea. DWI represents the meteorological characteristics, such as humidity (relative and effective), temperature and wind speed, and we integrated nine logistic regression models of the past into one national model. One national integrated model of the spring and fall is respectively $[1+{\exp}\{-(2.706+(0.088^*T_{mean})-(0.055^*Rh)-(0.023^*Eh)-(0.014^*W_{mean}))\}^{-1}]^{-1}$, $[1+{\exp}\{-(1.099+(0.117^*T_{mean})-(0.069^*Rh)-(0.182^*W_{mean}))\}^{-1}]^{-1}$ and all weather variables significantly (p<0.01) affected the probability of forest fire occurrence in the overall regions. The accuracy of the model in the spring and fall is respectively 71.7% and 86.9%. One integrated national model showed 10% higher accuracy than nine logistic regression models when it is applied weather data with 66 random sampling in forest fire event days. These findings would be necessary for the policy makers in the Republic of Korea for the prevention of forest fires.

Estimating Cumulative Distribution Functions with Maximum Likelihood to Sample Data Sets of a Sea Floater Model (해상 부유체 모델의 표본 데이터에 대해서 최대우도를 갖는 누적분포함수 추정)

  • Yim, Jeong-Bin;Yang, Won-Jae
    • Journal of Navigation and Port Research
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    • v.37 no.5
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    • pp.453-461
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    • 2013
  • This paper describes evaluation procedures and experimental results for the estimation of Cumulative Distribution Functions (CDF) giving best-fit to the sample data in the Probability based risk Evaluation Techniques (PET) which is to assess the risks of a small-sized sea floater. The CDF in the PET is to provide the reference values of risk acceptance criteria which are to evaluate the risk level of the floater and, it can be estimated from sample data sets of motion response functions such as Roll, Pitch and Heave in the floater model. Using Maximum Likelihood Estimates and with the eight kinds of regulated distribution functions, the evaluation tests for the CDF having maximum likelihood to the sample data are carried out in this work. Throughout goodness-of-fit tests to the distribution functions, it is shown that the Beta distribution is best-fit to the Roll and Pitch sample data with smallest averaged probability errors $\bar{\delta}(0{\leq}\bar{\delta}{\leq}1.0)$ of 0.024 and 0.022, respectively and, Gamma distribution is best-fit to the Heave sample data with smallest $\bar{\delta}$ of 0.027. The proposed method in this paper can be expected to adopt in various application areas estimating best-fit distributions to the sample data.

Development of a Failure Probability Model based on Operation Data of Thermal Piping Network in District Heating System (지역난방 열배관망 운영데이터 기반의 파손확률 모델 개발)

  • Kim, Hyoung Seok;Kim, Gye Beom;Kim, Lae Hyun
    • Korean Chemical Engineering Research
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    • v.55 no.3
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    • pp.322-331
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    • 2017
  • District heating was first introduced in Korea in 1985. As the service life of the underground thermal piping network has increased for more than 30 years, the maintenance of the underground thermal pipe has become an important issue. A variety of complex technologies are required for periodic inspection and operation management for the maintenance of the aged thermal piping network. Especially, it is required to develop a model that can be used for decision making in order to derive optimal maintenance and replacement point from the economic viewpoint in the field. In this study, the analysis was carried out based on the repair history and accident data at the operation of the thermal pipe network of five districts in the Korea District Heating Corporation. A failure probability model was developed by introducing statistical techniques of qualitative analysis and binomial logistic regression analysis. As a result of qualitative analysis of maintenance history and accident data, the most important cause of pipeline damage was construction erosion, corrosion of pipe and bad material accounted for about 82%. In the statistical model analysis, by setting the separation point of the classification to 0.25, the accuracy of the thermal pipe breakage and non-breakage classification improved to 73.5%. In order to establish the failure probability model, the fitness of the model was verified through the Hosmer and Lemeshow test, the independent test of the independent variables, and the Chi-Square test of the model. According to the results of analysis of the risk of thermal pipe network damage, the highest probability of failure was analyzed as the thermal pipeline constructed by the F construction company in the reducer pipe of less than 250mm, which is more than 10 years on the Seoul area motorway in winter. The results of this study can be used to prioritize maintenance, preventive inspection, and replacement of thermal piping systems. In addition, it will be possible to reduce the frequency of thermal pipeline damage and to use it more aggressively to manage thermal piping network by establishing and coping with accident prevention plan in advance such as inspection and maintenance.

Development of Reliability-Based Design Program based on the MATLAB GUI Environment (MATLAB GUI 환경기반 신뢰성 설계기법의 개발)

  • Jeong, Shin-Taek;Ko, Dong-Hui;Park, Tae-Hun;Kim, Jeong-Dae;Cho, Hong-Yeon
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.22 no.6
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    • pp.415-422
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    • 2010
  • Development of the reliability-based design program in the GUI environment is inadequate for engineers familiar with the deterministic design to deal with the international design criterion based on the probabilistic design. In this study, the design program based on the GUI environment is developed in order to more efficiently input the design factor and more easily carry out the design works. The GUI environment is the GUIDE (Graphic User Interface Development Environment) tool supported by the latest MATALB version 7.1. In order to test the model reliability, the probabilities of failure (POF) on the breakwater armor block (AB) and gravity quay-wall (QW) in the sliding mode are computed using the model in the Level II and Level III. The POF are 55.4~55.7% for breakwater AB and 0.0006~0.0007% for gravity QW. A non-GUI environment program results of the POF are 55.6% for breakwater AB and 0.0018% for gravity QW. In comparison, the POF difference is negligible for breakwater AB because the exact input design parameters are available, whereas the large POF difference, but within the same order, for gravity QW can be explained by the difference of the input design factors because of the poor input data information.

A Study on Gesture Recognition using Edge Orientation Histogram and HMM (에지 방향성 히스토그램과 HMM을 이용한 제스처 인식에 관한 연구)

  • Lee, Kee-Jun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.12
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    • pp.2647-2654
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    • 2011
  • In this paper, the algorithm that recognizes the gesture by configuring the feature information obtained through edge orientation histogram and principal component analysis as low dimensional gesture symbol was described. Since the proposed method doesn't require a lot of computations compared to the existing geometric feature based method or appearance based methods and it can maintain high recognition rate by using the minimum information, it is very well suited for real-time system establishment. In addition, to reduce incorrect recognition or recognition errors that occur during gesture recognition, the model feature values projected in the gesture space is configured as a particular status symbol through clustering algorithm to be used as input symbol of hidden Markov models. By doing so, any input gesture will be recognized as the corresponding gesture model with highest probability.

A Study on Eigenspace Face Recognition using Wavelet Transform and HMM (웨이블렛 변환과 HMM을 이용한 고유공간 기반 얼굴인식에 관한 연구)

  • Lee, Jung-Jae;Kim, Jong-Min
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.10
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    • pp.2121-2128
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    • 2012
  • This paper proposed the real time face area detection using Wavelet transform and the strong detection algorithm that satisfies the efficiency of computation and detection performance at the same time was proposed. The detected face image recognizes the face by configuring the low-dimensional face symbol through the principal component analysis. The proposed method is well suited for real-time system construction because it doesn't require a lot of computation compared to the existing geometric feature-based method or appearance-based method and it can maintain high recognition rate using the minimum amount of information. In addition, in order to reduce the wrong recognition or recognition error occurred during face recognition, the input symbol of Hidden Markov Model is used by configuring the feature values projected to the unique space as a certain symbol through clustering algorithm. By doing so, any input face will be recognized as a face model that has the highest probability. As a result of experiment, when comparing the existing method Euclidean and Mahananobis, the proposed method showed superior recognition performance in incorrect matching or matching error.

A Simulation Model for the Study of the Territorial Behavior of Subterranean Termites (흰개미 테리토리행동 연구를 위한 시뮬레이션 모델)

  • Jeon, Won-Ju;Lee, Sang-Hee
    • Journal of the Korea Society for Simulation
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    • v.21 no.2
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    • pp.1-9
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    • 2012
  • Subterranean termites forage by constructing tunnel networks in soil and encounter food resources during tunnel excavation. Some species of termites can travel up to 150 m underground. They often travel to the surface to find wood cellulose to feed their colony, which in turn causes extensive damage to wooden architecture, such as timber-frame houses. This type of damage has been constantly increasing along with global warming because higher temperatures provide an ecological niche for termites. The damage is closely related to termite territory size and distribution. Recently, as a way to research termite control, the necessity of a mathematical model to simulate termite territory formation in relation to damage has increased. So far, however, few studies have been conducted on the development of a model because it is difficult to quantify or characterize the relationship between territorial behavior and field conditions including complicated environmental factors. In the present study, we suggest a simulation model of the territoriality of the Formosan subterranean termites, Coptotermes formosanus (Shiraki), and Reticulitermes flavipes (Kollar), based on empirical data. The model consists of 2 procedures. One describes tunnel network growth for each colony, and the other represents territoriality based on tunnel-tunnel interactions between different colonies. Using the model, we show changes in territorial competition according to the termination probability of tunnel growth.

Assessment of climate change impacts on uncertainty and sensitivity of paddy water requirement in South Korea using multi-GCMs (Multi-GCMs을 활용한 논벼 필요수량의 불확성 및 민감도 기후영향평가)

  • Yoo, Seung-Hwan;Lee, Sang-Hyun;Choi, Jin-Yong;Yoon, Kwangsik;Choi, Dongho
    • Proceedings of the Korea Water Resources Association Conference
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    • 2016.05a
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    • pp.516-516
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    • 2016
  • 기후변화는 농업생산량 감소와 식량 안보 문제와 같이 농업에 심각한 영향을 미칠 수 있다. 또한 기존의 농업수리 및 관개배수 시설 운영에 영향을 줄 수 있다. 따라서 지속가능한 농업 수자원 관리를 위해서는 기후변화의 영향을 고려한 장기적인 계획 수립이 필요하다. 따라서 본 연구에서는 논벼 지역의 설계용수량의 확률론적 분석을 통한 논벼 필요수량 및 설계용수량에 대한 기후변화영향 평가를 실시하였다. 이를 위해서 본 연구에서는 23개 GCM의 36개 산출물을 활용하여 Multi-model ensemble 구축하였다. 먼저 GCM별 증발산량과 유효우량을 산정한 결과 중부지역에서는 IPSL-CM5A 모델의 기후변화자료를 활용할 경우 증발산량과 유효우량이 타 GCM 모델들과 비하여 크게 산정되었다. 남부지역에서는 CanESM2 모델을 적용할 경우 가장 많은 증발산량과 유효우량이 모의되는 것으로 나타났다. 이처럼 GCM별로 다양한 결과가 모의되기 때문에 농업시설 설계에 적용되는 설계용수량의 경우 안전성을 위하여 Multi-GCM models을 활용할 필요가 있다. Multi-model ensemble의 RCP 4.5와 RCP 8.5 시나리오를 적용한 결과, 모든 경우에서 1995s(1981-2014)에 비해 설계용수량은 점차적으로 증가하는 것으로 나타났다. 평균 증가율은 RCP 4.5에서 중부지역이 9.4%, 남부지역이 6.0% 증가하는 것으로 나타난 반면, RCP 8.5에서는 중부지역이 11.1%, 남부지역이 8.2% 증가하는 것으로 나타났다. 또한 여러 GCM 산출물간의 불확실성은 RCP 4.5보다는 RCP 8.5 시나리오가, 중부 지역보다는 남부 지역이, 논벼 증발산량 보다는 유효우량이 더 큰 것으로 분석되었다. 본 연구는 향후 미래 가뭄 위험성을 최소화하기 위한 농업 수자원관리 전략수립에 활용될 수 있을 것이다. 또한 본 연구결과는 기후변화 영향 평가에 있어서 적합한 GCM 자료를 선택하는데 있어, 불확실성을 가늠할 수 있는 유용한 척도로 이용될 수 있을 것으로 기대된다.

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Ecological Assessment Technique of Connectivity to Disconnected Floodplains by Levee (격리차단된 제내지 하천환경의 생태적 연계성 평가 기술)

  • Cho, Kang-Hyun;Jin, Seung-Nam;Cho, Hyunsuk
    • Proceedings of the Korea Water Resources Association Conference
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    • 2017.05a
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    • pp.7-7
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    • 2017
  • 범람파동 개념에 따르면 하도와 홍수터의 횡적 연결성은 하천 생태계의 생물다양성과 생산성 증대에 중요한 역할을 한다. 제방에 의하여 제내지 홍수터가 하도와 차단된 우리나라 하천에서 생태적 서비스를 증대하기 위해서 횡적 연결성을 복원하는 기술 개발이 필요하다. 횡적 연결성의 복원 기술을 개발하기 위해서는 우선 하도와 홍수터 사이에 생태적 연결성의 현황을 파악하고 연결성을 저해하는 요인을 진단하는 평가 기술 개발이 시급히 요청되고 있다. 따라서 본 연구에서는 제방에 의하여 차단된 제내지 하천환경에서 수리적, 생태적 횡적 연결성을 평가하고 진단하는 기술을 개발하고 연결성 회복 방안을 제안하고자 한다. 차단된 제내지 하천환경 평가는 1) 지리정보시스템을 이용하여 차단된 하천공간을 탐색하고, 2) 탐색된 전체 재내지에서 원격평가에 의하여 간편하게 횡적 연결성 평가를 실시하고, 3) 선정된 특정 제내지 대상지에서 현장평가에 의하여 상세하게 연결성을 평가하는 순서로 수행된다. 차단된 하천공간의 획정은 홍수가 범람할 수 있는 제내지 공간을 잠재적 하천공간으로 정의하고 수치표고모델 (DEM)과 하천기본계획의 30년 빈도 홍수위 자료를 이용하여 제내지 홍수터를 탐색하였다. 제내지 홍수터의 원격 연결성평가는 지리정보시스템에서 수치지도와 토지피복도 등 공간자료를 이용하여 수리 및 서식처 환경성, 제방 차단성과 하도 및 육상 연결성을 평가하고 원격평가 결과를 토대로 현장평가 대상지를 선정하였다. 횡적 연결성의 현장평가를 위하여 크게 하도-홍수터 연결성과 제내지 서식처 보존성으로 평가 항목을 선정하였다. 또한 연결성 평가는 수리연결성과 생물연결성으로, 서식처 보존성 평가는 습지유지율, 습지보존성, 육역지보존성을 세부항목으로 구성하였다. 평가 항목별로 5 등급의 평가 기준에 따라서 평가 점수를 부여하고 평가 총점을 산출하여 최종 연결성 평가 등급을 5 단계로 구분하였다. 현장평가를 위한 MS Access 기반 소프트웨어를 개발하여, 데이터 입력과 관리 및 평가 결과 산출과 비교를 편리하게 하였다. 개발된 제내지 하천환경 평가법을 청미천과 만경강에 적용하여 검증하였다. 개발된 평가법을 바탕으로 차단된 제내지 하천환경에서 연결성 회복에 따른 어류와 식생의 분포를 예측하는 수리생태 결합모델을 개발하였다. 먼저 차단된 제내지에서 연결 수로를 복원하여 유속, 수심 분포를 준이차 수리수문 모델로 예측하였다. 예측된 수리 환경에 따라서 지표어종의 서식처 적합도 지수 (HSI)를 이용하여 서식 분포 확률을 모의하였다. 또한 일반화가법모델 (GAM)을 이용하여 환경구배에 의한 우점식생의 분포를 예측하였다. 차단된 제내지 하천환경의 생태적 연계성 평가 기술을 기반으로 제방제거, 제방후퇴, 제방고 하강, 수문 및 연결수로 개선, 생물이동 저해 장벽 제거 등의 다양한 복원기술이 개발되어야 할 것으로 생각된다.

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