• Journal of Korean Society of Transportation
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• v.26 no.6
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• pp.61-70
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• 2008

The study proposed a new type of bus information, Real-time Bus Crowdedness (RBC) information, to meet various demands of users and improve the convenience level of using public transportation, while existing bus information provided by bus information systems(BIS) were limited to bus operating information such as predicted bus arrival time. To analyze the impacts of providing the proposed RBC information, stated preference(SP) survey was performed and a methodology of disaggregate analysis (e.g., binary logit) was applied to develop passenger choice models. Additionally, passenger choice models incorporating the heterogeneity of different user groups(i.e., by age or trip purposes) were developed to evaluate the different responses on RBC information. The results showed that providing RBC information was significantly related to users' bus choices and the responses of user groups were significantly different, especially the age group of more then 60 was most affected by the RBC information on their bus choices. Also trip purposes were significantly related to users' bus choices, for instance the impacts of providing RBC information was bigger for non-business trips(leisure/meet friend/personal business, shopping, hospital) compared to business trip.

• Korea journal of population studies
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• v.11 no.1
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• pp.1-13
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• 1988

This study examines the sampling bias that may have resulted from the large number of missing observations. Despite well-designed and reliable sampling procedures, the observed sample values in DSFH(Demographic Survey on Changes in Family and Household Structure, Japan) included many missing observations. The head administerd survey method of DSFH resulted in a large number of missing observations regarding characteristics of elderly non-head parents and their children. In addition, the response probability of a particular item in DSFH significantly differs by characteristics of elderly parents and their children. Furthermore, missing observations of many items occurred simultaneously. This complex pattern of missing observations critically limits the ability to produce an unbiased analysis. First, the large number of missing observations is likely to cause a misleading estimate of the standard error. Even worse, the possible dependency of missing observations on their latent values is likely to produce biased estimates of covariates. Two models are employed to solve the possible inference biases. First, EM algorithm is used to infer the missing values based on the knowledge of the association between the observed values and other covariates. Second, a selection model was employed given the suspicion that the probability of missing observations of proximity depends on its unobserved outcome.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.33-42
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• 2007

Accurate predictions of software release times, and estimation of the reliability and availability of a software product require quantification of a critical element of the software testing process : test coverage. This model called Enhanced non-homogeneous poission process(ENHPP). In this paper, exponential coverage and S-shaped model was reviewed, proposes the Kappa coverage model, which maked out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics and Kolmogorov distance, for the sake of efficient model, was employed. From the analysis of mission time, the result of this comparative study shows the excellent performance of Burr coverage model rather than exponential coverage and S-shaped model using NTDS data. This analysis of failure data compared with the Kappa coverage model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.12
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• pp.2311-2318
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• 2007

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. Accurate predictions of software release times, and estimation of the reliability and availability of a software product require Release times of a critical element of the software testing process : test coverage. This model called Enhanced non-homogeneous Poission process(ENHPP). In this paper, exponential coverage and S-shaped model was reviewed, proposes the Kappa coverage model, which make out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics and Kolmogorov distance, for the sake of efficient model, was employed. Numerical examples using real data set for the sake of proposing Kappa coverage model was employed. This analysis of failure data compared with the Kappaa coverage model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.7-14
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• 2006

The finite failure NHPP models proposed in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, we propose the Erlang reliability model, which can capture the increasing nature of the failure occurrence rate per fault. Equations to estimate the parameters of the Erlang finite failure NHPP model based on failure data collected in the form of inter-failure times are developed. For the sake of proposing shape parameter of the Erlang distribution, we used to the goodness-of-fit test of distribution. Data set, where the underlying failure process could not be adequately described by the existing models, which motivated the development of the Erlang model. Analysis of the failure data set which led us to the Erlang model, using arithmetic and Laplace trend tests, goodness-of-fit test, bias tests is presented.

• Journal of Korea Water Resources Association
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• v.51 no.2
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• pp.151-163
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• 2018

The objective of this study was to estimate LOADEST (LOAD Estimator) coefficients for simulating pollutant loads in ungauged watersheds. Regression models of LOADEST were used to simulate pollutant loads, and the multiple linear regression (MLR) was used for coefficients estimation on watershed characteristics. The fifth and third model of LOADEST were selected to simulate T-N (Total-Nitrogen) and T-P (Total-Phosphorous) loads, respectively. The results and statistics indicated that regression models based on LOADEST simulated pollutant loads reasonably and model coefficients were reliable. However, the results also indicated that LOADEST underestimated pollutant loads and had a bias. For this reason, simulated loads were corrected the bias by a quantile mapping method in this study. Corrected loads indicated that the bias correction was effective. Using multiple regression analysis, a coefficient estimation methods according to the watershed characteristic were developed. Coefficients which calculated by MLR were used in models. The simulated result and statistics indicated that MLR estimated the model coefficients reasonably. Regression models developed in this study would help simulate pollutant loads for ungauged watersheds and be a screen model for policy decision.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.3
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• pp.514-522
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• 2007

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this parer, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the Burr distribution reliability model, which making out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using real data set for the sake of proposing shape parameter of the Burr distribution was employed. This analysis of failure data compared with the Burr distribution model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

• Environmental and Resource Economics Review
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• v.28 no.4
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• pp.645-673
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• 2019

The hypothetical nature of stated preferences can lead to a hypothetical bias that might work as a normative pressure, influencing survey responses. This paper aims to test the impact of social desirability bias by comparing economic estimates based on both subjective and objective valuation questions. The case study is about an urban riverine restoration project in Deajeon, South Korea. As valuation methods both contingent valuation and choice experiments were comparatively applied. Based on a nationally representative sample of 1,000 respondents, the test results offered contrasting conclusions between two test approaches. Accroding to the estimation results based on the conventional valuation, the marginal willingness to pay estimates are 10,500 KRW from CV; and 18,600 KRW for improving water quality, 2,200 KRW for the inside view, 8,900 KRW for the outside view, and 5,800 KRW for biodiversity from CE. A segmentation-based approach is a conventionally used method, which showed a limited impact of social desirability on willingness to pay estimates. The alternative parameterization-based approach measures a model-wide impact of social desirability, proving a significant bias. Although the study positioned a cheap-talk statement before the valuation section of the survey questionnaires, which might have pre-screened the bias, the overall implications of the results suggest a caution in reducing and observing hypothetical bias. There might remain a significant and substantial hypothetical bias even after cheap-talk, particularly in situations with strong social desirability, so that the potential role of objective valuation questions is guaranteed.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.421-426
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• 2024

The Analytic Hierarchy Process (AHP) converts people's judgment criteria into objective numerical values using pairwise comparisons. However, the need for an excessive number of pairwise comparisons poses a problem. To mitigate this issue, most existing studies have utilized the process separation approach. The method of process separation devised in this study is a "separation and integration approach," where 1) the standard AHP process is used for evaluating judgment criteria, and 2) the Multi-Attributive Utility Technique (MAUT) is applied for comparing alternatives. This AHP-MAUT Hybrid model was applied to a real analysis case, specifically analyzing the transportation choices of commuters between Bundang and Gangnam Station in Gyeonggi Province. The results showed that the computational process was reduced by 42.03% when applying the Hybrid model compared to using the AHP model alone. Furthermore, the choice results of residents using the Hybrid model were compared with those using the standard AHP. The consistency between the two models' choices was 82.1%, indicating a significant level of consistency. In conclusion, this study contributes by presenting a simpler, more convenient, yet equally effective Hybrid model as a new decision-support system alternative to AHP.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1457-1461
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• 2009

기후변화로 인한 강수의 양과 패턴의 변화는 가뭄이나 홍수와 같은 극한사상의 발생가능성을 점차 증가시키고 있다. 이러한 극한사상의 발생에 대비하고자 기후변화가 가뭄이나 홍수에 미치는 영향 평가에 대한 연구가 전 세계적으로 활발히 진행 중이다. 이에 본 연구에서는 월 단위로 IPCC를 통해서 제공되는 Global Climate Model(GCM)중 하나인 BCM2 모형(A2 시나리오 선택)을 기반으로 기후변화가 한반도 가뭄에 미치는 영향평가 방안을 제시하고자 한다. 우선 전구단위 기후모형인 BCM2 모형을 격자단위 관측자료인 NCEP(National Centers for Environmental Prediction)자료를 이용하여 서울기상관측소 지점으로 축소하였다. 또한 축소된 강우자료의 편의를 보정하기 위하여 Quantile mapping 기법을 적용하였으며, 최종적으로 제시된 서울지점의 월 강우를 대상으로 표준강수지수(SPI)를 산정하여 기후변화가 서울지점의 가뭄에 미치는 영향을 평가하였다. 분석결과 기후변화를 고려할 경우, 전반적인 가뭄의 심도는 크게 깊어지지 않았으나 가뭄의 지속기간이 길어져 가뭄으로 인한 피해가 더욱 증가할 것으로 예상되었다.