• Title/Summary/Keyword: Series of Random Variables

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Design and Elucidation of Integrated Forecasting Model for Information Factor Analysis (정보인자분석(情報因子分析)을 위한 통합예측(統合豫測)모델의 설계(設計) 및 해석(解析))

  • Kim, Hong-Jae;Lee, Tae-Hui
    • Journal of Korean Society for Quality Management
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    • v.21 no.1
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    • pp.181-189
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    • 1993
  • Over the past two decades, forecasting has gained widespread acceptance as an integral part of business planning and decision making. Accurate forecasting is a prerequisite to successful planning. Accordingly, recent advances in forecasting techniques are of exceptional value to corporate planners. But most of forecasting mothods are reveal its limit and problem for precision and reliability duing to each relationship for raw data and possibility of explanation for each variable. Therefore, to construct the Integrated Forecasting Model(IFM) for Information Factor Analysis, it shoud be considered that whether law data has time lag and variables are explained. For this. following several method can be used : Least Square Method, Markov Process, Fibonacci series, Auto-Correlation, Cross-Correlation, Serial Correlation and Random Walk Theory. Thus, the unified property of these several functions scales the safety and growth of the system which may be varied time-to-time.

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Exploration of CHAID Algorithm by Sampling Proportion

  • Park, Hee-Chang;Cho, Kwang-Hyun
    • 한국데이터정보과학회:학술대회논문집
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    • 2003.10a
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    • pp.215-228
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    • 2003
  • Decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud dection, data reduction and variable screening, interaction effect identification, category merging and discretizing continuous variable, etc. CHAID(Chi-square Automatic Interaction Detector), is an exploratory method used to study the relationship between a dependent variable and a series of predictor variables. CHAID modeling selects a set of predictors and their interactions that optimally predict the dependent measure. In this paper we explore CHAID algorithm in view of accuracy and speed by sampling proportion.

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Warranty cost anlaysis for multi-component systems with imperfect repair

  • Park, Minjae
    • International Journal of Reliability and Applications
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    • v.15 no.1
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    • pp.51-64
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    • 2014
  • This paper develops a warranty cost model for complex systems with imperfect repair within a warranty period by addressing a practical case that the first inter-failure interval is longer than any other inter-failure intervals. The product is in its best condition before the first failure if repair is imperfect. After the imperfect repair, other inter-failure intervals which are explained by renewal processes, are stochastically smaller than the first inter-failure interval. Based on this idea, we suggest the failure-interval-failure-criterion model. In this model, we consider two random variables, X and Y where X represents failure intervals and Y represents failure criterion. We also obtain the distribution of the number of failures and conduct the warranty cost analysis. We investigate different types of warranty cost models, reliabilities and other measures for various systems including series-parallel configurations. Several numerical examples are discussed to demonstrate the applicability of the methodologies derived in the paper.

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Testing the domestic financial data for the normality of the innovation based on the GARCH(1,1) model

  • Lee, Tae-Wook;Ha, Jeong-Cheol
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.3
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    • pp.809-815
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    • 2007
  • Since Bollerslev(1986), the GARCH model has been popular in analysing the volatility of the financial time series. In real data analysis, practitioners conventionally put the normal assumption on the innovation random variables of the GARCH model, which is often violated. In this paper, we analyse the domestic financial data based on the GARCH(1,1) model and among existing normality tests, perform the Jarque-Bera test based on the residuals. It is shown that the innovation based on the GARCH(1,1) model dose not follow the normality assumption.

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Vulnerability Assessment for Fine Particulate Matter (PM2.5) in the Schools of the Seoul Metropolitan Area, Korea: Part II - Vulnerability Assessment for PM2.5 in the Schools (인공지능을 이용한 수도권 학교 미세먼지 취약성 평가: Part II - 학교 미세먼지 범주화)

  • Son, Sanghun;Kim, Jinsoo
    • Korean Journal of Remote Sensing
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    • v.37 no.6_2
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    • pp.1891-1900
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    • 2021
  • Fine particulate matter (FPM; diameter ≤ 2.5 ㎛) is frequently found in metropolitan areas due to activities associated with rapid urbanization and population growth. Many adolescents spend a substantial amount of time at school where, for various reasons, FPM generated outdoors may flow into indoor areas. The aims of this study were to estimate FPM concentrations and categorize types of FPM in schools. Meteorological and chemical variables as well as satellite-based aerosol optical depth were analyzed as input data in a random forest model, which applied 10-fold cross validation and a grid-search method, to estimate school FPM concentrations, with four statistical indicators used to evaluate accuracy. Loose and strict standards were established to categorize types of FPM in schools. Under the former classification scheme, FPM in most schools was classified as type 2 or 3, whereas under strict standards, school FPM was mostly classified as type 3 or 4.

Fuzzy reliability analysis of laminated composites

  • Chen, Jianqiao;Wei, Junhong;Xu, Yurong
    • Structural Engineering and Mechanics
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    • v.22 no.6
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    • pp.665-683
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    • 2006
  • The strength behaviors of Fiber Reinforced Plastics (FRP) Composites can be greatly influenced by the properties of constitutive materials, the laminate structures, and load conditions etc, accompanied by many uncertainty factors. So the reliability study on FRP is an important subject of research. Many achievements have been made in reliability studies based on the probability theory, but little has been done on the roles played by fuzzy variables. In this paper, a fuzzy reliability model for FRP laminates is established first, in which the loads are considered as random variables and the strengths as fuzzy variables. Then a numerical model is developed to assess the fuzzy reliability. The Monte Carlo simulation method is utilized to compute the reliability of laminas under the maximum stress criterion. In the second part of this paper, a generalized fuzzy reliability model (GFRM) is proposed. By virtue of the fact that there may exist a series of states between the failure state and the function state, a fuzzy assumption for the structure state together with the probabilistic assumption for strength parameters is adopted to construct the GFRM of composite materials. By defining a generalized limit state function, the problem is converted to the conventional reliability formula that enables the first-order reliability method (FORM) applicable in calculating the reliability index. Several examples are worked out to show the validity of the models and the efficiency of the methods proposed in this paper. The parameter sensitivity analysis shows that some of the mean values of the strength parameters have great influence on the laminated composites' reliability. The differences resulting from the application of different failure criteria and different fuzzy assumptions are also discussed. It is concluded that the GFRM is feasible to use, and can provide an effective and synthetic method to evaluate the reliability of a system with different types of uncertainty factors.

A Study on Setting Expected Targets for Satisfaction with the Frequency of Use of Construction Technology Information (건설기술정보의 활용 빈도 만족도에 대한 기대 목표치 설정에 관한 연구)

  • Seong-Yun Jeong
    • Journal of the Korean Society for Library and Information Science
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    • v.58 no.2
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    • pp.251-268
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    • 2024
  • Recently, with the implementation of the "e-Government Performance Management Guidelines," there is a growing demand for setting performance indicators for information systems. For systems that provide information services to the public, such as CODIL, it is not easy to set performance indicators. This study presented a research model that applies Monte Carlo simulation to set expected performance targets that can be achieved through CODIL based on objective evidence. Among the survey contents conducted from 2015 to 2023, the statistical characteristics of user satisfaction regarding the frequency of use of construction technology information provided by CODIL were designated as input variables. Future expected targets and confidence intervals from 2024 to 2026 were designated as outcome variables. The expected target value was measured by generating 5 simulation alternatives and 1,000 random numbers for each alternative. Next, the measured expected goals were interpreted and compared with the results of time series regression analysis measured in previous studies. Although, as in previous studies, the expected target value could not be predicted based on time series regression analysis that considers the correlation between years. However, compared to previous studies, this study can be considered a more accurate analysis result because it predicted the expected target value based on 5,000 input variables.

The Role of Economics, Politics and Institutions on Budget Deficit in ASEAN Countries

  • NGO, Minh Ngoc;NGUYEN, Loc Duc
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.9
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    • pp.251-261
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    • 2020
  • The paper examines the role of some determinants of economics, politics and institutions on the budget deficit volatility in some countries of the Association of South East Asian Nations (ASEAN) such as Indonesia, Thailand and Vietnam. The paper uses the fixed effects model (FEM) and the random effects model (REM) to investigate panel data of these countries in the period of 1990-2018. Moreover, the study also explores ordinary least square (OLS) to analyze time-series data for each country in the same period to make comparison among them. The economic data is collected from international financial statistics and world development indicators. The data on political variables are collected from International Country Risk Data Guide (ICRG). The empirical results both confirm that corruption and political stability are important indicators of budget deficit. Besides, the paper suggests authorities should pay more attention on improving the institutional setup of the economy in order to avoid high and unstable deficit. The findings offer new insight on the budget deficit in essence and suggest that the most important thing need to be done ahead is to strongly implement anti-corruption actions. By doing so, the status of budget deficit would be remarkably improved immediately.

Reliability Estimation of Solder Joint by Using Failure Probability Model (파손확률 모델을 이용한 솔더 조인트의 건전성 평가)

  • Myoung, No-Hoon;Lee, Ouk-Sub;Kim, Dong-Hyeok
    • Proceedings of the KSME Conference
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    • 2004.04a
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    • pp.365-370
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    • 2004
  • Generally, component and FR-4 board are connected by solder joint. Because material properties of components and FR-4 board are different, component and FR-4 board show different coefficients of thermal expansion (CTE) and thus strains in component and board are different when they are heated. That is, the differences in CTE of component and FR-4 board cause the dissimilarity in shear strain and solder joint' failure. The first order Taylor series expansion of the limit state function incorporating with Tresca failure criterion is used in order to estimate the failure probability of solder joints under heated condition. Using shear stresses and shear strains appeared on the solder joint, we estimate the failure probability of solder joints with the Tresca failure criterion. The effects of random variables such as CTE, distance of the solder joint from the neutral point(DNP), temperature variation and height of solder on the failure probability of the solder joint are systematically studied by using the failure probability model with first order reliability method(FORM).

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Relationship between Phase Properties, Significant Duration and PGA from the Earthquake Records of Mw 5.5~6.5 (Mw 5.5~6.5 지진동의 위상특성과 계속시간 및 PGA와의 관계)

  • Choi, Hang;Yoon, Byung Ick
    • Journal of the Earthquake Engineering Society of Korea
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    • v.23 no.1
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    • pp.55-70
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    • 2019
  • The phase properties of ground acceleration records from Mw 5.5~6.5 earthquakes are analyzed. The interrelationships between phase properties and significant durations, as well as PGA, are clarified through both of theoretical and empirical approaches. The probabilistic characteristics of phase information is also discussed based on previous studies and it is shown that circular normal distribution is the most appropriate probability distribution for the phase angle and phase difference. Whereas those variates can be modeled by Gaussian random variables. From the survey results on the frequency dependency of the phase statistics, a simple model is introduced, which is possible to express the frequency dependency of phase information. It is also shown that the significant duration can be controlled by appropriately chosen standard deviation of phase difference for 4~8Hz frequency band and additional consideration of phase scattering in higher frequency band through a series of Monte Carlo simulations. The source of phase scattering effect is also pointed out and discussed.