• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.84-92
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• 2021

Care services are a significant asset in human life. Care in its overall nature focuses on human needs and covers several aspects such as health care, homes, personal care, and education. In fact, care deals with many dimensions: physical, psychological, and social interconnections. Very little information is available on estimating the cost of care services that provided to orphans and abandoned children. Prediction of the cost of the care system delivered by governmental or non-governmental organizations to support orphans and abandoned children is increasingly needed. The purpose of this study is to analyze the care cost for orphanage organizations in Saudi Arabia to forecast the cost as well as explore the most influence factor on the cost. By using business analytic process that applied statistical and machine learning techniques, we proposed a model includes simple linear regression, Naive Bayes classifier, and Random Forest algorithms. The finding of our predictive model shows that Naive Bayes has addressed the highest accuracy equals to 87% in predicting the total care cost. Our model offers predictive approach in the perspective of business analytics.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.349-352
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• 2015

Size of building has a direct relationship with building cost, energy use and space maintenance cost. Therefore, minimizing building size during a project development is of paramount importance against such wastes. However, incautious reduction of building size may result in crowded space, and therefore harms the functionality despite the fact that building is supposed to satisfactorily support users' activity. A well-balanced design solution is, therefore, needed at an optimum level that minimizes building size in tandem with providing sufficient space to maintain functionality. For such design, architects and engineers need to be informed accurate and reliable space-use information. We present in this paper a conceptual framework of an agent-based space-use prediction simulation system that provides individual level space-use information over time in a building in consideration of project specific user information and activity schedules, space preference, ad beavioural rules. The information will accordingly assist architects and engineers to optimize space of the building as appropriate.

• 한국건설관리학회논문집
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• 제14권3호
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• pp.42-52
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• 2013

본 연구는 기존의 선형적인 공사비 예측방법의 한계를 극복하고 사례기반추론 (Case Based Reasoning, CBR)기법을 통해 기획단계의 실적정보를 활용하여 신뢰도 높은 공사비 예측 모델을 제시하는 것이 목적이다. 이를 위하여 사례기반추론 기법과 유전자알고리즘 (Genetic Algorithm, GA)의 선택연산을 복합적으로 활용한 스프레드시트 기반의 교량공사비 추론모델을 제시하였다. 추론모델의 검증을 위하여 국내 교량공사 시공사례 4건을 적용하였으며, 적용 결과 평균 8.69%의 오차율로 나타나 교량공사비의 예측 정확도가 타 분석방법과 비교하여 상대적으로 높은 것으로 파악하였다. 연구에서 제시된 교량공사비 예측모델은 초기 설계단계에서 상세제원에 대한 정보를 획득할 수 없을 경우에, 교량의 대표적 제원정보 만으로 공사비 선택범위를 최소화된 오차율로 예측할 수 있으므로, 개선된 보정 방법으로서 교량공사의 합리적인 개략공사비 산정에 활용될 수 있을 것으로 판단된다.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2006년도 정기학술발표대회 논문집
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• pp.137-142
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• 2006

비용과 공기는 수익과 직접적인 상관관계를 갖는 중요한 요소로 성공적인 프로젝트를 위해서는 이들에 대한 정확한 예측이 이루어져야 한다. 현재 최종 공사비와 공기 예측을 목적으로 EVMS(Earned Value Management System)가 범용적으로 활용되고 있지만, 기존에 제시된 공사비 및 공기 예측모텔은 선형적인 예측방식을 사용하기 때문에 예측결과가 부정확하고 시공업체의 성향, 프로젝트의 특성, 진도율에 따른 변화 등을 고려하지 못하는 한계가 있었다. 본 연구에서는 건설산업의 다양한 특성이 반영될 수 있도록 PB-S curve와 다중회귀분석을 이용한 진행단계별 공사비 및 공기의 기울기 예측모델을 제안하고 이를 동해 최종 공사비 및 공기를 예측하고자 한다. 이를 위하여 국내 건설업체로부터 23건의 도로공사 EVMS 자료를 활용하여 공사 진행단계별 기울기 예측을 위한 회귀분석방정식을 도출하고, 활용성을 검증하였다.

• 한국건축시공학회지
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• 제22권3호
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• pp.317-326
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• 2022

건설 분야에서 머신러닝(Machine learning)에 필요한 방대한 공사비 자료를 확보하는 데 어려움이 있어, 아직은 실용적으로 활용되지는 못하고 있다. 본 연구에서는 이러한 공사비 예측을 위하여 최신의 인공신경망(ANN) 방법을 사용하여, 공사비 예측성능을 향상 시키기 위한 방법을 제시하고자 한다. 특히 타겟변수를 로그 변환하는 방식, 피처스케일링 방식을 적용하고자 하였으며, 이들의 공사비 예측성능을 비교 분석하고자 한다. 이는 향후 다양한 조건을 갖는 공사비 예측과 적정 공사비 검증에 도움을 줄 수 있을 것으로 예측된다.

• ETRI Journal
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• 제38권5호
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• pp.807-817
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• 2016

A novel fast algorithm is suggested for a coding unit (CU) mode decision using pseudo rate-distortion based on a separated encoding structure in High Efficiency Video Coding (HEVC). A conventional HEVC encoder requires a large computational time for a CU mode prediction because prediction and transformation procedures are applied to obtain a rate-distortion cost. Hence, for the practical application of HEVC encoding, it is necessary to significantly reduce the computational time of CU mode prediction. As described in this paper, under the proposed separated encoder structure, it is possible to decide the CU prediction mode without a full processing of the prediction and transformation to obtain a rate-distortion cost based on a suitable condition. Furthermore, to construct a suitable condition to improve the encoding speed, we employ a pseudo rate-distortion estimation based on a Hadamard transformation and a simple quantization. The experimental results show that the proposed method achieves a 38.68% reduction in the total encoding time with a similar coding performance to that of the HEVC reference model.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2012년도 추계 학술논문 발표대회
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• pp.153-154
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• 2012

The accuracy of cost estimation at an early stage in school building project is one of the critical factors for successful completion. So many method and techniques have developed that can estimate construction cost using limited information available in the early stage. Among the techniques, Support Vector Machine(SVM) has received attention in various field due to its excellent capacity for self-learning and generalization performance. Therefore, the purpose of this study is to verify the applicability of cost prediction model based on SVM in school building project at the early stage. Data used in this study are 139 school building cost constructed from 2004 to 2007 in Gyeonggi-Do. And prediction error rate of 7.48% in support vector machine is obtained. So the results showed applicability of using SVM model for predicting construction cost of school building projects.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.510-515
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• 2011

Urban renewal projects, in the form of mega-projects, are being actively implemented both nationally and internationally to revitalize inactive cities. These programs, however, are difficult to manage efficiently due to their need for a large budget over a long period of time and due to conflicts with stockholders. Moreover, existing cost and duration management systems are structured with emphasis on the design and construction stage of unit projects, thus limiting their application to long-term mega-projects that are integrated with various facilities. To solve these problems, this study developed a web-based system that can collectively manage the cost and duration of mega-projects at a program level. The unit modules included in the system--CBS organization, construction cost and duration prediction, and total cost and duration prediction--can support decision-making at the early stage of the program. Furthermore, the modules, which include contract management, execution management, change management, and program progress management, support the program operations for its successful accomplishment. The web-based cost and duration management system developed in this study is expected to be used as a valuable tool that supports the successful accomplishment of mega-projects through their efficient management throughout their life cycle.

• 국제학술발표논문집
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• The 2th International Conference on Construction Engineering and Project Management
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• pp.653-661
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• 2007

Overseas construction projects tend to be more complex than domestic projects, being exposed to more external risks, such as politics, economy, society, and culture, as well as more internal risks from the project itself. It is crucial to have an early understanding of the project condition, in order to be well prepared in various phases of the project. This study compares a structural equation model and multiple regression analysis, in their capacity to predict cost performance of international construction projects. The structural equation model shows a more accurate prediction of cost performance than does regression analysis, due to its intrinsic capability of considering various cost factors in a systematic way.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2002년도 추계학술대회 논문집(I)
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• pp.376-381
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• 2002

In this study, we have analyzed the cost of korea high-speed rail project. The predicted cost in planning phase and adjustment data to 5th year are collected. Then, predicted cost is compared with adjustment in year/item/system base. We make a project history table for criteria to review project history and research ＆ development activity. We have developed CBS(cost breakdown structure) and allocated adjustment data to them. It is shown that cost prediction related to research St development activity in planning phase is relatively correct.