• 제목/요약/키워드: cost prediction

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A CBR-BASED COST PREDICTION MODEL FOR THE DESIGN PHASE OF PUBLIC MULTI-FAMILY HOUSING CONSTRUCTION PROJECTS

  • TaeHoon Hong;ChangTaek Hyun;HyunSeok Moon
    • 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.

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H.264/AVC를 위한 효율적인 인트라 예측 기법 (Complexity Reduction of Intra Prediction in H.264/AVC)

  • 이남숙;이재헌
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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    • pp.125-128
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    • 2003
  • In this paper, we propose two methods for complexity reduction of intra prediction in H.264/AVC. One is skipping of intra prediction using inter prediction cost at current macroblock in current P picture, average of intra prediction cost in previous I picture, and average of inter prediction cost in previous P picture. The other is skipping of intra 16$\times$16 prediction using intra 4$\times$4 prediction cost and modes. As a result, complexity of intra prediction in P picture and that of intra 16$\times$16 prediction in intra prediction macroblock can be reduced by about 80~99% and 50~93%, respectively.

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회귀분석을 이용한 건축물 해체공사비 예측모델 (Cost Prediction Model for Building Demolition Work by Using Regression Analysis)

  • 김태훈;김영현;조규만
    • 한국건축시공학회지
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    • 제21권2호
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    • pp.105-112
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    • 2021
  • 국내 해체시장 규모는 꾸준히 증가되고 있는 반면, 해체공사비 예측 연구는 미흡한 실정이다. 이에 본 연구에서는 해체공사비 변동에 영향을 미치는 다양한 속성을 반영한 공사비 예측 모델을 제시하고자 하였다. 이를 위하여 기존 문헌고찰과 전문가 자문을 바탕으로 13개의 영향요인과 실적공사비 데이터를 수집하였으며, 회귀분석을 통해 2개의 예측모델을 구축하고 예측정확도를 평가하였다. 그 결과, 약 6~12%의 평균 오차율을 보였으며, 예측 모델로서의 활용 가능성을 모색할 수 있었다. 본 연구 결과는 향후 국내 해체공사의 적정 공사비산정 및 관련 기준 정비에 기여할 수 있을 것이다.

정성변수를 고려한 공공아파트 기획단계 공사비 예측모델 (Cost Prediction Model using Qualitative Variables focused on Planning Phase for Public Multi-Housing Projects)

  • 지성민;현창택;문현석
    • 한국건설관리학회논문집
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    • 제13권2호
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    • pp.91-101
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    • 2012
  • 공공아파트 프로젝트의 기획단계에서 수행되는 적정 공사비 예측은 기획부터 유지관리까지 전(全) 단계에 걸쳐서 영향을 미치게 되므로 명확한 예측기준 및 방법이 제시되어야 한다. 그러나 현재까지 다양한 다중회귀모델을 활용한 공사비 예측 방법이 개발되어 왔으나, 정성변수를 포함하여 공사비를 예측하는 방법에 대한 연구는 부족한 상황이다. 따라서 본 연구에서는 기획단계 활용을 위한 정성변수를 포함하는 공사비 예측모델을 개발하고자 하였다. 이를 위하여 공사비 영향요인을 분석 및 추출하고, 회귀분석을 위한 독립변수를 선정하였다. 그리고 정성변수를 포함하는 공사비 예측모델을 개발하며 사례적용을 통한 검증을 실시하였다. 개발된 공사비 예측모델과 "RESAMPLING 기법"을 사용하여 구조형식별 공사비 가산비율을 제시하였다. 본 연구에서 제시한 더미회귀모델과 가산비율을 활용하면, 일반적인 공사비 예측과 함께 동일한 평형, 세대수, 연면적에서 평면형식과 구조형식을 변경시켰을 때의 공사비 예측이 가능할 것으로 기대된다.

서포트 벡터 머신을 이용한 건설업 안전보건관리비 예측 모델 (Construction Safety and Health Management Cost Prediction Model using Support Vector Machine)

  • 신성우
    • 한국안전학회지
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    • 제32권1호
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    • pp.115-120
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    • 2017
  • The aim of this study is to develop construction safety and health management cost prediction model using support vector machine (SVM). To this end, theoretical concept of SVM is investigated to formulate the cost prediction model. Input and output variables have been selected by analyzing the balancing accounts for the completed construction project. In order to train and validate the proposed prediction model, 150 data sets have been gathered from field. Effects of SVM parameters on prediction accuracy are analyzed and from which the optimal parameter values have been determined. The prediction performance tests are conducted to confirm the applicability of the proposed model. Based on the results, it is concluded that the proposed SVM model can effectively be used to predict the construction safety and health management cost.

사례기반 추론을 이용한 암 환자 진료비 예측 모형의 개발 (Development of a Medial Care Cost Prediction Model for Cancer Patients Using Case-Based Reasoning)

  • 정석훈;서용무
    • Asia pacific journal of information systems
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    • 제16권2호
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    • pp.69-84
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    • 2006
  • Importance of Today's diffusion of integrated hospital information systems is that various and huge amount of data is being accumulated in their database systems. Many researchers have studied utilizing such hospital data. While most researches were conducted mainly for medical diagnosis, there have been insufficient studies to develop medical care cost prediction model, especially using machine learning techniques. In this research, therefore, we built a medical care cost prediction model for cancer patients using CBR (Case-Based Reasoning), one of the machine learning techniques. Its performance was compared with those of Neural Networks and Decision Tree models. As a result of the experiment, the CBR prediction model was shown to be the best in general with respect to error rate and linearity between real values and predicted values. It is believed that the medical care cost prediction model can be utilized for the effective management of limited resources in hospitals.

실적공사비에 의한 지하철 공사비 예측모형에 관한 연구 (A Study on the Prediction-Formulas of Approximate Estimate Based on Actual Work Cost for Subway)

  • 박종혁;전영배;박홍태
    • 한국재난정보학회 논문집
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    • 제9권1호
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    • pp.11-21
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    • 2013
  • 본 연구는 2004년 이후 도입된 실적 공사비 제도에 의하여 착공된 지하철 건설공사를 대상으로 실적공사비, 공사규모 그리고 시간을 고려하여 공사비를 예측하는 식을 제시하였다. 11개의 지하철공사 자료를 이용하여 지하철 공사비 예측을 위한 비용-규모 지수 n(신뢰범위:0.5~0.7)을 구한 결과, 총공사비 0.713, 순공사비 0.77로 도출되었다. 본 연구에서 제시한 공사비 예측 식 모델은 향후 지하철 공사 적용 현장의 사업기획, 예비조사, 타당성조사, 기본설계 단계에서 개산 공사비를 추정하는데 효과적으로 적용할 수 있을 것이다.

부분 태그와 작은 데이터 크기에 기반한 저비용 연산결과 예측기 구조 (Cost Effective Value Prediction Microarchitecture using Partial-Tag and Narrow-Width Operands)

  • 최병수;이동익
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2001년도 하계종합학술대회 논문집(2)
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    • pp.265-268
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    • 2001
  • In this paper we investigate the implementation cost of value prediction methods for high performance micro-processors, and propose a new value prediction microarchitecture with low cost. After simulation, we found that the proposed microarchitecture can decrease the implementation cost by 36% to 50% and with slight performance degradation (less than 5%) .

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생애주기비용 예측 기반 건물재료 경제성 평가 및 선정 (Evaluation and Selection of Building Materials based on Life Cycle Cost Prediction)

  • 안정환;임진강;오민호;이재욱
    • 한국BIM학회 논문집
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    • 제5권2호
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    • pp.34-45
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    • 2015
  • As buildings become larger and more complicated, construction costs have increased with a considerable effect on buildings' Life Cycle Cost (LCC). However, there has been little consideration on economic aspects in the selection of construction materials due to limited information on the materials and dependency in architects' experience and inefficiency in cost estimation, causing design changes, increase in maintenance cost, difficulty in budgeting, and decrease in building performance. To solve these problems, this study proposed a BIM-based material selection model which reflects the comprehensive economic efficiency of building materials. Our cost prediction model can estimates the material-related cost during the entire building life cycle. Furthermore, we implemented the proposed model in connection with BIM, which can analyze and compare LCC by material. Through the validation of the model, we could confirm the necessity of LCC-based material selection in comparison with the conventional cost-centered material selection.

Psychophysical cost function of joint movement for arm reach posture prediction

  • 최재호;김성환;정의승
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 1994년도 춘계공동학술대회논문집; 창원대학교; 08월 09일 Apr. 1994
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    • pp.561-568
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    • 1994
  • A man model can be used as an effective tool to design ergonomically sound products and workplaces, and subsequently evaluate them properly. For a man model to be truly useful, it must be integrated with a posture prediction model which should be capable of representing the human arm reach posture in the context of equipments and workspaces. Since the human movement possesses redundant degrees of freedom, accurate representation or prediction of human movement was known to be a difficult problem. To solve this redundancy problem, a psychophysical cost function was suggested in this study which defines a cost value for each joint movement angle. The psychophysical cost function developed integrates the psychophysical discomfort of joints and the joint range availability concept which has been used for redundant arm manipulation in robotics to predict the arm reach posture. To properly predict an arm reach posture, an arm reach posture prediction model was then developed in which a posture configuration that provides the minimum total cost is chosen. The predictivity of the psychophysical cost function was compared with that of the biomechanical cost function which is based on the minimization of joint torque. Here, the human body is regarded as a two-dimensional multi-link system which consists of four links ; trunk, upper arm, lower arm and hand. Real reach postures were photographed from the subjects and were compared to the postures predicted by the model. Results showed that the postures predicted by the psychophysical cost function closely simulated human reach postures and the predictivity was more accurate than that by the biomechanical cost function.