Determining Attribute Weights in a CBR Model for Early Cost Prediction of Structural Systems

Doğan, Sevgi Zeynep; Arditi, David; Günaydın, Hakan

doi:10.1061/(asce)0733-9364(2006)132:10(1092)

Cited by 104 publications

(53 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…some of the methods that were used in the previous studies are as follows: (i) analogical methods such as Cbr (Koo et al, 2010;ryu, 2007;Dogan et al, 2006); (ii) statistical methods such as multiple regression analysis (mra) (Koo et al, 2010;lowe et al, 2006;phaobunjong, 2002); (iii) repetitive learning methods such as the artificial neural network (ann) (Koo et al, 2010;rifat, 2004;Hegazy and ayed, 1998); and (iv) optimization methods such as Ga (Koo et al, 2010;Dogan et al, 2006). it was found that the aforementioned methodologies should be applied to the proper fields according to the objective of using methodologies or distinct characteristics, such as the applied fields, data, and optimization level.…”

Section: Comparison Of Several Methodsmentioning

confidence: 99%

“…although ann was most superior among several methodologies that calculate the attribute weight, a Cbr model should be optimized for the calculation of the attribute weight, where the target is based on the prediction accuracy using Ga. in the study conducted by Dogan et al (2006), Ga was adapted to deduce the attribute weight where the target was not based on prediction accuracy but case similarity.…”

Section: Comparison Of Several Methodsmentioning

confidence: 99%

See 1 more Smart Citation

A Study on the Development of a Cost Model Based on the Owner's Decision Making at the Early Stages of a Construction Project

Koo¹,

Hong

Hyun

et al. 2010

International Journal of Strategic Property Management

View full text Add to dashboard Cite

Decision making at the early stages of a construction project has a significant impact on the project, and various scenarios created based on the owner's requirements should be considered for the decision making. At the early stages of a construction project, the information regarding the project is usually limited and uncertain. As such, it is difficult to plan and manage the project (especially cost planning). Thus, a cost model that could be varied according to the owner's requirements was developed. The cost model that was developed in this study is based on the case‐based reasoning (CBR) methodology. The model suggests cost estimation with the most similar historical case as a basis for the estimation. In this study, the optimization process was also conducted, using genetic algorithms that reflect the changes in the number of project characteristics and in the database of the model according to the owner's decision making. Two optimization parameters were established: (1) the minimum criteria for scoring attribute similarity (MCAS); and (2) the range of attribute weights (RAW). The cost model proposed in this study can help building owners and managers estimate the project budget at the business planning stage. Santruka Sprendimu priemimas ankstyvuoju statybos projekto etapu turi didele itaka projektui ir ivairiems scenarijams, remiantis savininko reikalavimais, kuriu turi būti laikomasi priimant sprendimus. Ankstyvaisiais statybos projekto etapais informacijos apie projekta paprastai yra nedaug ir ji nera patikima. Del to sudetinga planuoti ir taisyti projekta (ypač išlaidu planavima). Todel šio tyrimo metu buvo sukurtas kainos modelis, kuris galetu būti keičiamas atsižvelgiant i savininko poreikius. Kainos modelis, kuris buvo sukurtas šio tyrimo metu, remiasi atveju analize, pagrista argumentu metodika (angl. CBR). Modelis siūlo samatinius skaičiavimus su panašiausiais ankstesniais atvejais, kurie yra skaičiavimo pagrindas. Šio tyrimo metu procesas buvo optimizuotas naudojant genetinius algoritmus, rodančius projektu skaičiaus kitima tam tikro modelio duomenu bazeje pagal savininko priimamus sprendimus. Buvo nustatyti du optimizavimo parametrai: 1) minimalūs kriterijai veiksniu panašumui ivertinti (angl. MCAS); 2) veiksniu svoriu vertinimo intervalas (angl. RAW). Kainos modelis, pasiūlytas šiame tyrime, gali padeti pastatu savininkams ir valdytojams ivertinti projekto biudžeta verslo planavimo etape.

show abstract

Section: Comparison Of Several Methodsmentioning

confidence: 99%

Section: Comparison Of Several Methodsmentioning

confidence: 99%

A Study on the Development of a Cost Model Based on the Owner's Decision Making at the Early Stages of a Construction Project

Koo¹,

Hong

Hyun

et al. 2010

International Journal of Strategic Property Management

View full text Add to dashboard Cite

show abstract

“…This provides a simple way to measure construction costs, given that, according to most studies, there are non-linear relationships between cost and factors that affect it [32][33][34][35]. An interesting example of the use of CBR in the cost estimation process can be a model using the AHP method to determine the weights of criteria, proposed by [26] or the CBR model using genetic algorithms to estimate the construction costs [36] or unit cost of residential construction projects [37]. Models are also being created that predict both construction time and cost at an early stage of a construction project [38].…”

Section: Literature Reviewmentioning

confidence: 99%

Cost Calculation of Construction Projects Including Sustainability Factors Using the Case Based Reasoning (CBR) Method

Leśniak

Zima

2018

Sustainability

View full text Add to dashboard Cite

Abstract:The idea of sustainable development and the resulting environmentally friendly attitudes are increasingly used in construction projects. Designing in accordance with the principles of sustainable development has an impact on the costs of construction works. The authors of this paper proposed an approach to estimate the costs of sports field construction using the Case Based Reasoning method. In their analysis, they distinguished 16 factors that affect the cost of a construction project and are possible to already be described at an early stage of its preparation. The original elements of the work include: consideration of such environmental factors as the environmental impact of the building, materials used, the impact of the facility on the surroundings affecting the amount of implementation costs and development of own database containing 143 construction projects that are related to sports fields. In order to calculate the similarity of cases, different calculation formulas were applied depending on the type of data (quantitative, qualitative, uncertain, no data). The obtained results confirmed that the CBR method based on historical data and using criteria related to sustainable development may be useful in cost estimation in the initial phase of a construction project. Its application to the calculation of the costs that are related to the implementation of sports fields generates an error of 14%, which is a very good result for initial calculations. In the short run, such factors as the impact of the object and the type of materials that are used from the perspective of their influence on the environment may be decisive as far as the costs determined in the life cycle of the building are concerned, as well as the lowest costs of the building construction ensuring the appropriate quality and respect for the environment.

show abstract

“…Several researches have applied CBR for prediction in different business domains, including the early cost prediction of structural systems [5], the predicting high risk software components [6] and etc. Our previous research proposed a casebased prediction mechanism to predict IS outsourcing success using genetic algorithms (GA) to support the retrieval of similar cases [7].…”

Section: Case-based Prediction Modelmentioning

confidence: 99%

Customer Relationship Management in Healthcare Service – An Integrated DSS Framework for Patient Loyalty

Hsu

Chiu

2009

Studies in Computational Intelligence

View full text Add to dashboard Cite

Abstract. Patient loyalty is a critical criterion for healthcare customer relationship management (CRM). An integrated framework with a case-based prediction model and a constraint-based optimization model is proposed to support the decision making of healthcare providers. This research first adopts a case-based prediction mechanism to forecast the possible loyalty level. We also proposes a constraint-based optimization approach as a subsequent mechanism to determine the optimum values of case features that may lead to the optimal patient loyalty. The potential use of this framework helps a decision maker allocate resources to increase the loyalty level for the given target patient segmentation.

show abstract

Determining Attribute Weights in a CBR Model for Early Cost Prediction of Structural Systems

Cited by 104 publications

References 7 publications

A Study on the Development of a Cost Model Based on the Owner's Decision Making at the Early Stages of a Construction Project

A Study on the Development of a Cost Model Based on the Owner's Decision Making at the Early Stages of a Construction Project

Cost Calculation of Construction Projects Including Sustainability Factors Using the Case Based Reasoning (CBR) Method

Customer Relationship Management in Healthcare Service – An Integrated DSS Framework for Patient Loyalty

Contact Info

Product

Resources

About