• 제목/요약/키워드: Process of Hierarchical Analysis

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준모수적 계층적 선택모형에 대한 베이지안 방법 (A Bayesian Method to Semiparametric Hierarchical Selection Models)

  • 정윤식;장정훈
    • 응용통계연구
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    • 제14권1호
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    • pp.161-175
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    • 2001
  • 메타분석(Meta-analysis)은 서로 독립적으로 연구되어진 결과들을 전체적인 하나의 결과로 도출하기 위해 사용되어지는 통계적 방법이다. 이러한 통계적 방법을 설명할 모형으로는 선택모형(selection model)을 포함한 계층적 모형(hierarchical model)을 사용하며, 이러한 모형들은 베이지안 메타분석에 유용한 것으로 알려져 있다. 그러나, 메타분석의 자료들은 일반적으로 출판편의(publication bias)를 갖고 있으므로 이를 극복하고자 가중함수(weight function)를 이용하여 분포함수를 새롭게 정의하여 사용한다. 최근에 Silliman(1997)은 계층적 모형(hierarchical model)에 가중함수를 첨부한 계층적 선택모형(hierarchical selection model)을 정의하고 모수적 베이지안 방법을 제시하였다. 본 연구에서는 미관측된 연구효과에 디리슈레 과정 사전분포(Dirichlet process prior)를 적용한 준모수적 계층적 선택모형(semiparametric hierarchical selection models)을 소개한다. 여기서 제시된 준모수적 계층적 선택모형을 베이지안 방법으로 추정하기 위하여 마코프 연쇄 몬테칼로(Markov chain Monte Carlo)방법을 이용한다. 제시된 방법을 적용하기 위하여 실제 자료(Johnson, 1993)인 충치를 예방하기 위한 두 가지의 예방약의 효과에 대한 차이를 비교하기 위해 얻어진 12개의 연구를 이용하여 메타분석을 한다.

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Assessment of geological hazards in landslide risk using the analysis process method

  • Peixi Guo;Seyyed Behnam Beheshti;Maryam Shokravi;Amir Behshad
    • Steel and Composite Structures
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    • 제47권4호
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    • pp.451-454
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    • 2023
  • Landslides are one of the natural disasters that cause a lot of financial and human losses every year It will be all over the world. China, especially. The Mainland China can be divided into 12 zones, including 4 high susceptibility zones, 7 medium susceptibility zones and 1 low susceptibility zone, according to landslide proneness. Climate and physiography are always at risk of landslides. The purpose of this research is to prepare a landslide hazard map using the Hierarchical Analysis Process method. In the GIS environment, it is in a part of China watershed. In order to prepare a landslide hazard map, first with Field studies, a distribution map of landslides in the area and then a map of factors affecting landslides were prepared. In the next stage, the factors are prioritized using expert opinion and hierarchical analysis process and nine factors including height, slope, slope direction, geological units, land use, distance from Waterway, distance from the road, distance from the fault and rainfall map were selected as effective factors. Then Landslide risk zoning in the region was done using the hierarchical analysis process model. The results showed that the three factors of geological units, distance from the road and slope are the most important have had an effect on the occurrence of landslides in the region, while the two factors of fault and rainfall have the least effect The landslide occurred in the region.

계층구조 접근에 의한 복합시스템 고장진단 기법 (Fault Diagnosis Method of Complex System by Hierarchical Structure Approach)

  • 배용환;이석희
    • 한국정밀공학회지
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    • 제14권11호
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    • pp.135-146
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    • 1997
  • This paper describes fault diagnosis method in complex system with hierachical structure similar to human body structure. Complex system is divided into unit, item and component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. Fault diagnosis system can forecast faults in a system and decide from current machine state signal information. Comparing with other diagnosis system for single fault, the developed system deals with multiple fault diagnosis comprising Hierarchical Neural Network(HNN). HNN consists of four level neural network, first level for item fault symptom classification, second level for item fault diagnosis, third level for component symptom classification, forth level for component fault diagnosis. UNIX IPC(Inter Process Communication) is used for implementing HNN wiht multitasking and message transfer between processes in SUN workstation with X-Windows(Motif). We tested HNN at four units, seven items per unit, seven components per item in a complex system. Each one neural newtork operate as a separate process in HNN. The message queue take charge of information exdhange and cooperation between each neural network.

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Hierarchical Attention Network를 활용한 주제에 따른 온라인 고객 리뷰 분석 모델 (Analysis of the Online Review Based on the Theme Using the Hierarchical Attention Network)

  • 장인호;박기연;이준기
    • 한국IT서비스학회지
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    • 제17권2호
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    • pp.165-177
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    • 2018
  • Recently, online commerces are becoming more common due to factors such as mobile technology development and smart device dissemination, and online review has a big influence on potential buyer's purchase decision. This study presents a set of analytical methodologies for understanding the meaning of customer reviews of products in online transaction. Using techniques currently developed in deep learning are implemented Hierarchical Attention Network for analyze meaning in online reviews. By using these techniques, we could solve time consuming pre-data analysis time problem and multiple topic problems. To this end, this study analyzes customer reviews of laptops sold in domestic online shopping malls. Our result successfully demonstrates over 90% classification accuracy. Therefore, this study classified the unstructured text data in the semantic analysis and confirmed the practical application possibility of the review analysis process.

An Agglomerative Hierarchical Variable-Clustering Method Based on a Correlation Matrix

  • Lee, Kwangjin
    • Communications for Statistical Applications and Methods
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    • 제10권2호
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    • pp.387-397
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    • 2003
  • Generally, most of researches that need a variable-clustering process use an exploratory factor analysis technique or a divisive hierarchical variable-clustering method based on a correlation matrix. And some researchers apply a object-clustering method to a distance matrix transformed from a correlation matrix, though this approach is known to be improper. On this paper an agglomerative hierarchical variable-clustering method based on a correlation matrix itself is suggested. It is derived from a geometric concept by using variate-spaces and a characterizing variate.

Using DEA and AHP for Hierarchical Structures of Data

  • Pakkar, Mohammad Sadegh
    • Industrial Engineering and Management Systems
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    • 제15권1호
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    • pp.49-62
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    • 2016
  • In this paper, we propose an integrated data envelopment analysis (DEA) and analytic hierarchy process (AHP) methodology in which the information about the hierarchical structures of input-output data can be reflected in the performance assessment of decision making units (DMUs). Firstly, this can be implemented by extending a traditional DEA model to a three-level DEA model. Secondly, weight bounds, using AHP, can be incorporated in the three-level DEA model. Finally, the effects of incorporating weight bounds can be analyzed by developing a parametric distance model. Increasing the value of a parameter in a domain of efficiency loss, we explore the various systems of weights. This may lead to various ranking positions for each DMU in comparison to the other DMUs. An illustrative example of road safety performance for a set of 19 European countries highlights the usefulness of the proposed approach.

기술우선도 결정을 위한 상호영향 계층분석모형의 개발 (Development of a Cross-impact Hierarchical Model for Deciding Technology Priority)

  • 권철신;조근태
    • 한국경영과학회지
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    • 제27권1호
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    • pp.1-17
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    • 2002
  • The objective of this paper is to develop a new priority setting algorithm that considers the cross-impact of the future technology alternatives and that satisfies the final goal of the technology management through multi-hierarchy evaluation criteria. By combining the Analytic Hierarchy Process (AHP) model, which is a well-known priority setting model, and Cross Impact Analysis (CIA) model, which is a technological forecasting method that considers cross-impact among R&D Items, we developed an Integrated Cross-Impact Hierarchical (CIH) model, which sets the priority by considering technological forecasting and technology dependency simultaneously. A step-by-step numerical example of the model developed here is presented as backup of its practicality.

계층적 설계 환경에서 일관된 타이밍 분석을 위한 분할 및 제한 조건 생성 기술 개발 (Partitioning and Constraints Generation for the Timing Consistency in the Hierarchical Design Method)

  • 한상용
    • 한국정보처리학회논문지
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    • 제7권1호
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    • pp.215-223
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    • 2000
  • VLSI의 집적도가 계속 증가되고 있어 복잡한 칩 설계를 위해서는 설계의 계층성 이용이 매우 중요하다. 계층설계는 대규모의 설계 데이터를 기능의 계층성을 이용하여 분할 설계하기 때문에 오랫동안 이용되어 왔다. 그러나, 계층 설계에서는 분할 설게후 다시 통합하기 때문에 원래의 설계 데이터와 분할${\cdot}$통합한 설계 데이터 사이에 타이밍 분석 결과의 차이가 발생할 수 있고 이는 칩 개발 시간을 지연시키는 주요 요인이 된다. 본 논문에서는 계층설계에서 타이밍 문제를 공식화하였고, 타이밍 분석시 림ㅅ설계와 차이가 나는 원인들을 분석하였다. 일관된 타이밍 분석이란 개념을 정의하였고 일관성유지를 위한 분할 기법을 제안하였으며, 제안한 알고리즘을 구현하여 기존의 설계툴에 접목하여 일관성 향상을 얻었다.

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통계적 실험계획 및 분석: Gate Poly-Silicon의 Critical Dimension에 대한 계층적 분산 구성요소 및 웨이퍼 수준 균일성 (Statistical Design of Experiments and Analysis: Hierarchical Variance Components and Wafer-Level Uniformity on Gate Poly-Silicon Critical Dimension)

  • 박성민;김병윤;이정인
    • 대한산업공학회지
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    • 제29권2호
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    • pp.179-189
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    • 2003
  • Gate poly-silicon critical dimension is a prime characteristic of a metal-oxide-semiconductor field effect transistor. It is important to achieve the uniformity of gate poly-silicon critical dimension in order that a semiconductor device has acceptable electrical test characteristics as well as a semiconductor wafer fabrication process has a competitive net-die-per-wafer yield. However, on gate poly-silicon critical dimension, the complexity associated with a semiconductor wafer fabrication process entails hierarchical variance components according to run-to-run, wafer-to-wafer and even die-to-die production unit changes. Specifically, estimates of the hierarchical variance components are required not only for disclosing dominant sources of the variation but also for testing the wafer-level uniformity. In this paper, two experimental designs, a two-stage nested design and a randomized complete block design are considered in order to estimate the hierarchical variance components. Since gate poly-silicon critical dimensions are collected from fixed die positions within wafers, a factor representing die positions can be regarded as fixed in linear statistical models for the designs. In this context, the two-stage nested design also checks the wafer-level uniformity taking all sampled runs into account. In more detail, using variance estimates derived from randomized complete block designs, Duncan's multiple range test examines the wafer-level uniformity for each run. Consequently, a framework presented in this study could provide guidelines to practitioners on estimating the hierarchical variance components and testing the wafer-level uniformity in parallel for any characteristics concerned in semiconductor wafer fabrication processes. Statistical analysis is illustrated for an experimental dataset from a real pilot semiconductor wafer fabrication process.

객체지향모델링 과정에서 계층적 유즈케이스(Use Case) 분석을 통한 클래스 도출 및 정의 (Design of Class Model Using Hierarchical Use Case Analysis for Object-Oriented Modeling)

  • 이재우
    • 한국산학기술학회논문지
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    • 제10권12호
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    • pp.3668-3674
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    • 2009
  • 유즈케이스 다이어그램은 사용자와 시스템간의 상호작용을 정의하는데 사용되어 진다. 소프트웨어 개발에 있어서 사용자의 요구사항을 도출하고 정의하는 것은 가장 중요한 일중에 하나이다. 본 논문에서는 클래스 추출 및 정의를 위하여 계층화 된 유즈케이스 모델링 과정을 제안하였다. 본 논문에서 제안하는 모델링 과정에서는 먼저, 여러 계층에 걸쳐서 유즈케이스 다이어그램을 정의하고 다음단계로서 각 계층별 클래스를 추출하고자 하였다. 즉, 소프트웨어 개발에 있어서의 사용자 요구사항 정의단계에서 도출된 유즈케이스 다이어그램과 클래스 다이어그램들의 상호작용을 비교 검증함으로써 보다 효율적인 객체지향모델링 과정을 수행할 수 있게 된다.