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- W2017709557 abstract "성공적인 자산관리시스템의 도입은 풍부하고도 신뢰할 수 있는 데이터와 함께 시작된다. 그러나 현실에서는 알려지지 않은 다양한 원인에서 비롯되는 관측 오차들은 항상 존재하기 마련이다. 이는 관리자의 유지보수활동을 방해하며 파손과정이나 생애주기비용 예측결과의 신뢰성에도 악영향을 미친다. 무엇보다도 관리자가 자신의 손으로 직접 조사한 자료를 믿지 못하는 모순된 결과를 낳는다. 이런 현상은 도로포장관리분야에서 특히나 심각하다. 도로관리자들은 이러한 사실에 대해 충분히 인식하고 있으나, 현실적으로 오차 없는 조사를 수행한다는 것은 하나의 큰 도전이라고도 할 수 있다. 이러한 점들을 고려하여 본 연구에서는 포장표면 조사자료에 포함된 오류 및 잠재오차를 보정하기 위한 통계적 방법론을 제시하고자 하였다. 방법론으로는 오차의 구조 및 신뢰도를 고려할 수 있도록 확률분포이론에 근거한 두 가지 기법(샘플기준법과 분포기준법)을 제안하였다. 제안된 방법론은 국도에서 수집된 포장상태자료들을 활용하여 적용 가능성을 살펴보았으며, 그 결과 눈에 보이는 오류들만을 제거하는 일반적인 방법론으로는 포장자료에 포함된 불확실성을 충분히 고려할 수 없음을 확인하였다. 제안된 방법론은 도로자산관리에 필요한 다양한 분석의 신뢰성을 개선하는데 유용하게 활용될 수 있을 것이다. Successful implementation of infrastructure asset management system can be started with rich and reliable data. However, measurement errors in the data have always existed in the real world caused for many unknown reasons. It disturbs maintenance activities of agencies, and makes negative effects to reliability of research results on forecasting deterioration process and life cycle cost. Above all, it makes a contradiction that road agencies cannot believe their inspection data surveyed by their hands. It is particularly serious in the road pavement management field. Although road agencies are well recognized the fact, inspecting without measurement error would be a great challenge. Considering the facts, this paper aimed to suggest statistical error processing methods to correct latent error included in pavement surface inspection data. As alternatives, this paper suggested two methods based on probability distribution to consider structure of error and reliability of the data. The suggested methods were empirically tested by using pavement inspection data from Korean National Highway. As the result, this paper confirmed that conventional error processing that just removes only visible errors is not enough to cover uncertainty in pavement deterioration process. The suggested methods would be useful for improving reliability of analysis results required for road infrastructure asset management." @default.
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- W2017709557 date "2012-11-15" @default.
- W2017709557 modified "2023-10-18" @default.
- W2017709557 title "Correction of Latent Errors in Pavement Deterioration Data using Statistical Methods" @default.
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