• 한국농공학회지
• /
• 제45권6호
• /
• pp.183-193
• /
• 2003

Most construction works on the soft ground adopt instrumentation to manage settlement and stability of the embankment. The rapid progress of the information technologies and the digital data acquisition on the soft ground instrumentation has led to the fast-growing amount of data. Although valuable information about the behaviour of the soft ground may be hiding behind the data, most of the data are used restrictedly only for the management of settlement and stability. One of the critical issues on soft ground instrumentation is the long-term settlement prediction. Some observational settlement analysis methods are used for this purpose. But the reliability of the analysis results is remained in vague. The knowledge could be discovered from a large volume of experiences on the observational settlement analysis. In this article, we present a database to store settlement records and data mining procedure. A large volume of knowledge about observational settlement prediction were collected from the database by applying the filtering algorithm and knowledge discovery algorithm. Statistical analysis revealed that the reliability of observational settlement analysis depends on stay duration and estimated degree of consolidation.

• 한국안전학회지
• /
• 제16권3호
• /
• pp.117-124
• /
• 2001

This paper introduces m analysis framework and procedure for the support of the cognitive error analysis of emergency tasks in nuclear poler plants. The framework provides a new perspective in the utilization of influencing factors into error prediction. The framework can be characterized by two features. First, influencing factors that affect the occurrence of human error me classified into three groups, i.e., task characteristic factors(TCF), situation factors(SF), and performance assisting factors(PAF). This classification aims to support error prediction from the viewpoint of assessing the adequacy of PAF under given TCF and SF. Second, the assessment of influencing factors is made by each cognitive function. Through this, influencing factors assessment and error prediction can be made in an integrative way according to each cognitive function. In addition, it helps analysts identify vulnerable cognitive functions and error factors, and obtain specific nor reduction strategies. The proposed framework was applied to the error analysis of the bleed and feed operation of nuclear emergency tasks.

• 한국해양공학회지
• /
• 제26권2호
• /
• pp.39-47
• /
• 2012

The objective of this study was to develop a strength prediction model using a polynomial regression analysis based on the experimental results obtained from ninety samples. As the results of a correlation analysis between various mixing factors and unconfined compressive strength using SPSS (statistical package for the social sciences), the governing factors in the strength of lightweight soil were found to be the crumb rubber content, bottom ash content,and water-cement ratio. After selecting the governing factors affecting the strength through the correlation analysis, a strength prediction model, which consisted of the selected governing factors, was developed using the polynomial regression analysis. The strengths calculated from the proposed model were similar to those resulting from laboratory tests (R2=87.5%). Therefore, the proposed model can be used to predict the strength of lightweight mixtures with various mixing ratios without time-consuming experimental tests.

• 한국소음진동공학회논문집
• /
• 제22권2호
• /
• pp.123-129
• /
• 2012

It was previously suggested the design sensitivity analysis based on transmissibility function to identify the most sensitive response location over a small design modification. On the other hand, energy isoclines were used to predict the fatigue damage with acceleration response only. Both of previous studies commonly tackle the engineering problem using the acceleration response alone such that it may be possible to investigate the relationship between sensitivity analysis and accumulated fatigue damage. In this paper, it is suggested the novel method of vibration fatigue prediction using design sensitivity analysis to enhance the accuracy of predicted accumulated fatigue. Uni-axial vibration testing is performed with a simple notched specimen and the prediction of fatigue damage is conducted using accelerations measured at different locations. It can be concluded that the accuracy of predicted fatigue damage is proportional to the sensitivity index of the responsible location.

• 대한조선학회논문집
• /
• 제40권2호
• /
• pp.57-62
• /
• 2003

The block assembly of ship consists of a certain type of heat processes such as cutting, bending, welding, residual stress relaxation and fairing. The residual deformation due to welding is inevitable at each assembly stage. The geometric inaccuracy caused by the welding deformation tends to preclude the introduction of automation and mechanization and needs the additional man-hours for the adjusting work at the following assembly stage. To overcome this problem, a distortion control method should be applied. For this purpose, it is necessary to develop an accurate prediction method which can explicitly account for the influence of various factors on the welding deformation. The validity of the prediction method must be also clarified through experiments. This paper proposes a simplified analysis method to predict the welding deformation of panel block structure. For this purpose, a simple prediction model for fillet welding deformations has been derived based on numerical and experimental results through the regression analysis. On the basis of these results, the simplified analysis method has been applied to some examples to show its validity.

• 디지털콘텐츠학회 논문지
• /
• 제19권6호
• /
• pp.1105-1114
• /
• 2018

최근 국내 음원 시장의 성장 속도가 두드러짐에 따라 음원 흥행 예측의 필요성이 커졌다. 본 논문에서는 인터넷 기사, SNS 등 소셜 데이터와 멜론 주간차트 진입 순위의 상관관계를 분석하여 음원 흥행의 예측 지표를 제안한다. 남자 가수와 여자 가수 각각에 대하여 총 10가지 항목의 소셜 데이터를 수집하였고, 군집 분석을 실시하였다. 이를 통해 남자 가수와 여자 가수 각각의 유의미한 음원 흥행 예측 지표를 발견하였다.

• Computers and Concrete
• /
• 제17권2호
• /
• pp.173-188
• /
• 2016

Generally, thermal stress induced by hydration heat causes cracking in mass concrete structures, requiring a thorough control during the construction. The prediction of the thermal stress is currently undertaken by means of numerical analysis despite its lack of reliability due to the properties of concrete varying over time. In this paper, a method for the prediction of thermal stress in concrete structures by adjusting thermal stress measured by a thermal stress device according to the degree of restraint is proposed to improve the prediction accuracy. The ratio of stress in concrete structures to stress under complete restraint is used as the degree of restraint. To consider the history of the degree of restraint, incremental stress is predicted by comparing the degree of restraint and the incremental stress obtained by the thermal stress device. Furthermore, the thermal stresses of wall and foundation predicted by the proposed method are compared to those obtained by numerical analysis. The thermal stresses obtained by the proposed method are similar to those obtained by the analysis for structures with internally as well as externally strong restraint. It is therefore concluded that the prediction of thermal stress for concrete structures with various boundary conditions using the proposed method is suggested to be accurate.

• 한국지반공학회:학술대회논문집
• /
• 한국지반공학회 2005년도 춘계 학술발표회 논문집
• /
• pp.185-190
• /
• 2005

In this study, a probabilistic prediction model for debris flow occurrence was developed using a logistic regression analysis. The model can be applicable to metamorphic rocks and granite area. In order to develop the prediction model, detailed field survey and laboratory soil tests were conducted both in the northern and the southern Gyeonggi province and in Sangju, Gyeongbuk province, Korea. The six landslide triggering factors were selected by a logistic regression analysis as well as several basic statistical analyses. The six factors consist of two topographic factors and four geological and geotechnical factors. The model assigns a weight value to each selected factor. The verification results reveal that the model has 86.5% of prediction accuracy. Therefore, it is possible to predict landslide occurrence in a probabilistic and quantitative manner.

• Journal of the Optical Society of Korea
• /
• 제13권2호
• /
• pp.279-285
• /
• 2009

Prediction of glucose concentration in the interstitial fluid (ISF) based on mid-infrared absorption spectroscopy was examined at the glucose fundamental absorption band of 1000 - 1500/cm (10 - 6.67 um) using multi-component analysis. Simulated ISF samples were prepared by including four major ISF components. Sodium lactate had absorption spectra that interfere with those of glucose. The rest NaCl, KCl and $CaCl_2$ did not have any signatures. A preliminary experiment based on Design of Experiment, an optimization method, proved that sodium lactate influenced the prediction accuracy of glucose. For the main experiment, 54 samples were prepared whose glucose and sodium lactate concentration varied independently. A partial least squares regression (PLSR) analysis was used to build calibration models. The prediction accuracy was dependent on spectrum preprocessing methods, and Mean Centering produced the best results. Depending on calibration sample sets whose sodium lactate had different concentration levels, the standard error prediction (SEP) of glucose ranged $17.19{\sim}21.02\;mg/dl$.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
• /
• 제15권8호
• /
• pp.596-600
• /
• 2009

검증과 확인을 통한 소프트웨어의 효율적인 관리를 지원하기 위하여 객체지향 메트릭 기반의 결함 예측 모형이 많이 제안되고 있다. 제안된 모형은 주로 로지스틱 회귀분석으로 개발하였다. 그리고 개발된 모형의 결함 예측 정확도는 60${\sim}$70%이었다. 본 논문에서는 기존 결함 예측 모형의 효과를 확인하기 위하여 이클립스 3.3을 대상으로 개발된 모형과 유사한 방법으로 실험을 하였다. 실험 결과 모형의 정확성은 약 40%이었다. 이는 주장된 예측력보다 많이 낮은 수치이었다. 또한 단순 로지스틱 회귀분석이 다중 로지스틱 회귀분석보다 높은 예측력을 보였다.