• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 추계학술대회논문집
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• pp.59-65
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• 2005

The research is an objective which prevents a construction noise by developing prediction program on utility, helps comprehension of construction noise by case study. The program developed with Visual Basic of the Excel Logic. The standard noise is a data with report of the construction machine (National Institute of Environmental Research), construction noise of sound pressure level applied the distance decrease of the point source. The decrease effect of the barrier noise wall used the data of 5, 10, 15, 20dB where the diffraction is reflected. used a program, case study is suggested Prevention method to prevent noise of construction site.

• 디지털산업정보학회논문지
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• 제17권1호
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• pp.109-115
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• 2021

The number of freshmen at universities is decreasing due to the recent decline in the school-age population, and the survival of many universities is threatened. To overcome this situation, universities are seeking ways to use big data within the school to improve the quality of education. A study on the prediction of dropout students is a representative case of using big data in universities. The dropout prediction can prepare a systematic management plan by identifying students who will drop out of school due to reasons such as dropout or expulsion. In the case of actual on-campus data, a large number of missing values are included because it is collected and managed by various departments. For this reason, it is necessary to construct a model by effectively reflecting the missing values. In this study, we propose a university student dropout prediction model based on eXtreme Gradient Boost that can be applied to data with many missing values and shows high performance. In order to examine the practical applicability of the proposed model, an experiment was performed using data from C University in Chungbuk. As a result of the experiment, the prediction performance of the proposed model was found to be excellent. The management strategy of dropout students can be established through the prediction results of the model proposed in this paper.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.203-211
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• 2009

Korean public owners who order public multi-family housing construction projects have yet to gain access to a model for predicting construction cost. For this reason, their construction cost prediction is mainly dependent upon historic data and experience. In this paper, a cost-prediction model based on Case-Based Reasoning (CBR) in the design phase of public multi-family housing construction projects was developed. The developed model can determine the total construction cost by estimating the different Building, Civil, Mechanical, Electronic and Telecommunication, and Landscaping work costs. Model validation showed an accuracy of 97.56%, confirming the model's excellent viability. The developed model can thus be used to predict the construction cost to be shouldered by public owners before the design is completed. Moreover, any change orders during the design phase can be immediately applied to the model, and various construction costs by design alternative can be verified using this model. Therefore, it is expected that public owners can exercise effective design management by using the developed cost prediction model. The use of such an effective cost prediction model can enable the owners to accurately determine in advance the construction cost and prevent increase or decrease in cost arising from the design changes in the design phase, such as change order. The model can also prevent the untoward increase in the duration of the design phase as it can effectively control unnecessary change orders.

• 대한원격탐사학회지
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• 제23권4호
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• pp.287-295
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• 2007

광물자원 분포도는 아직 발견되지 않은 광상의 부존 가능성을 공간적 분포로 나타내는 일종의 예측 주제도에 해당된다. 이러한 예측 주제도는 예측 가능성이 높은 지역의 공간적 위치뿐만 아니라 예측 능력에 대한 검증 정보가 함께 제시되어야 주제도의 신뢰성을 판단할 수 있다 이 연구의 목적은 미래의 광상 발견과 관련된 예측 확률을 추정하기 위해 교차 검증을 통해 얻어지는 예측비율곡선을 응용하는데 있다. 지화학 자료를 이용한 열수 맥상 형태의 Au-Ag 광상을 예측도 작성 사례 연구를 통해, 예측 확률 추정 과정과 결과의 해석을 예시하였다. 사례연구 수행 결과, 예측 주제도의 해석을 위해서는 검증을 통한 정량적 근거가 함께 제시되어야 함을 확인할 수 있었다. 이 연구를 통해 얻어지는 정량적 검증 자료는 추후 광상 개발 관련비용 분석과 환경 영향 추정에도 이용될 수 있을 것으로 기대된다.

• 보건교육건강증진학회지
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• 제13권2호
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• pp.130-166
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• 1996

As compared with body height and body weight by ages and sexes, by means of the data reported under other researchers from 1967 to 1994 for 33 years, this study obtained the estimate value of body height and body weight by ages and sexes for the same period, and figured out prediction value of body height and body weight in the ages of between 6 and 14 from 1995 to 2000. These surveys and measurements took for one year from October 1st 1994 to September 30th. As shown in the 〈Table 1〉, in order to calculate the establishment, estimate value and prediction value of the chronological regression model of body height and body weight, by well-grounded 17 representative research papers, this research statistically tested propriety of liner regression model by the residual analysis in advance of being reconciled to simple liner regression model by the autonomous variable-year and the subordinate variable-body weight and measured prediction value, theoretical value from 1962 to 1994 by means of 2nd or 3rd polynomial regression model, with this redult did prediction value from 1995 to 2000. 1. Chronological Change of Body Height and Body Weight The analysis result from regression model of the chronological body height and body weight for the aged 6 - 16 in both sexes ranging from 1962 to 1994, corned from the 〈Table 2-20〉. On the one hand, the measurement value of respective researchers had a bit changes by ages with age growing, but the other hand, theoretical value, prediction value showed the regular increase by the stages and all values indicated a straight line on growth and development with age growing. That is, in case of the aged 6, males had 109.93cm in 1962 and females 108.93cm, but we found the increase that males had 1I8.0cm, females 1I3.9cm. In theoretical value, prediction value, males showed the increase from 109.88cm to 1I7.89cm and females from 109.27cm to 1I5.64cm respectively. There was the same inclination toward all ages. 2. Comparision to Measurement Value and Prediction Value of Body Height and Body Weight in 1994 As shown in the 〈Table 21〉, in case of body height, measurement value and prediction value of body height and body weight by ages and sexes almost showed the similiar inclination and poor grade, in case of body weight, prediction value in males had a bit low value by all ages, and prediction value in females had a high value in adolescence, to the contrary, a low value in adult. 3. Prediction Value of Body Height and Body Weight from 1995 to 2000 This research showed that body height and body weight remarkably increased in adolescence but slowly in adult. This study represented that Korean physique was on the increase and must be measured continually hereafter.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2007년도 한국지능정보시스템학회
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• pp.389-398
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• 2007

Case-based reasoning (CBR) is one of the most popular prediction techniques for medical diagnosis because it is easy to apply, has no possibility of overfitting, and provides a good explanation for the output. However, it has a critical limitation - its prediction performance is generally lower than other artificial intelligence techniques like artificial neural networks (ANNs). In order to obtain accurate results from CBR, effective retrieval and matching of useful prior cases for the problem is essential, but it is still a controversial issue to design a good matching and retrieval mechanism for CBR systems. In this study, we propose a novel approach to enhance the prediction performance of CBR. Our suggestion is the simultaneous optimization of feature weights, instance selection, and the number of neighbors that combine using genetic algorithms (GAs). Our model improves the prediction performance in three ways - (1) measuring similarity between cases more accurately by considering relative importance of each feature, (2) eliminating redundant or erroneous reference cases, and (3) combining several similar cases represent significant patterns. To validate the usefulness of our model, this study applied it to a real-world case for evaluating cytological features derived directly from a digital scan of breast fine needle aspirate (FNA) slides. Experimental results showed that the prediction accuracy of conventional CBR may be improved significantly by using our model. We also found that our proposed model outperformed all the other optimized models for CBR using GA.

• 품질경영학회지
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• 제47권1호
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• pp.187-198
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• 2019

Purpose: In this study, a reliability prediction based reliability growth management is suggested especially for the early development phase of a system and the case study of surveillance system is given. Methods: The proposed reliability prediction based reliability growth management procedures consists of 7 Steps. In Step 1, the stages for reliability growth management are classified according to the major design changes. From Step 2 to Step 5, system reliability is predicted based on reliability structures and the predicted reliabilities of subsystems (Level 2) and modules (Level 3). At each stage, by comparing the predicted system reliability with that of the previous stage, the reliability growth of the system is checked in Step 6. In Step 7, when the predicted value of sustem reliability does not satisfy the reliability goal, some design alternatives are considered and suggested to improve the system reliability. Results: The proposed reliability prediction based reliability growth management can be an efficient alternative for managing reliability growth of a system in its early development phase. The case study shows that it is applicable to weapon system such as a surveillance system. Conclusion: In this study, the procedures for a reliability prediction based reliability growth management are proposed to satisfy the reliability goal of the system efficiently. And it is expected that the use of the proposed procedures would reduce, in the test and evaluation phase, the number of corrective actions and its cost as well.

• 산업공학
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• 제11권1호
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• pp.175-182
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• 1998

The maintainability prediction of an underwater military system is considered. A general and parctical prediction method for maintainability using MIL-HDBK-472 is presented. We develop a computer program to predict MTTR of an underwater military system. A case study is made to explain the proposed maintainability prediction method.

• Communications for Statistical Applications and Methods
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• 제15권3호
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• pp.343-351
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• 2008

By supervised learning with p predictors, we frequently obtain a prediction function of the form $y\;=\;f(x_1,...,x_p)$. When $p\;{\geq}\;3$, it is not easy to understand the inner structure of f, except for the case the function is formulated as additive. In this study, we propose to use p simple graphs for visual understanding of complex prediction functions produced by several supervised learning engines such as LOESS, neural networks, support vector machines and random forests.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.189-191
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• 2005

In the scalable extension of H.264/AVC, the codec is based on a layered approach to enable spatial scalability. In each layer, the basic concepts of motion compensated prediction and intra prediction are employed as in standard H.264/AVC. Additionally inter-layer prediction algorithm between successive spatial layers is applied to remove redundancy. In the inter-layer prediction, as the prediction we can use the signal that is the upsampled signal of the lower resolution layer. In this case, coding efficiency can be variable as the kinds of interpolation filter. In this paper, we investigate the approach to select the interpolation filter for residual signal in order to optimal prediction.