Reviewing of the Simulation Models in Cost Management of the Construction Projects

Al-Zwainy, Faiq M. S.; Amer, Reem; Khaleel, Tareq A.

doi:10.28991/cej-2016-00000063

Cited by 6 publications

(3 citation statements)

References 12 publications

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“…Identifying factors that negatively affect labour productivity in construction projects has been a major concern for managers [32,38]. After careful analysis of the top influential factors cited by researchers [10,12], [21][22][23], [39][40][41][42][43], the factors that appeared repeatedly were identified and extracted.…”

Section: Questionnaire Survey Analysismentioning

confidence: 99%

“…Parametric model was developed in the early 1960s, it has been used to find the relationship between the response and one or more factors, usually by applying regression analysis to the parameters [31]. [32] Developed a parametric equation based on multiple linear regression (MLR) analysis to model the labour productivity of marble floor finishing works in Iraq.100 data including 10 influencing factors were collected and used to predict productivity, good performance, and a high correlation was obtained, indicating a good relationship between the response and the factors, and the model can be reliably used to estimate productivity. In another study conducted by [33] to estimate the percentage loss or increase in construction labour productivity, 14 influencing factors were defined and used to develop a regression model, the author argued that the proposed model can accurately predict construction labour productivity.…”

Section: Introductionmentioning

confidence: 99%

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Improvement of Productivity in Buildings Construction

Dehchar,

Boudjellal,

Bouabaz

2023

Selected Scientific Papers - Journal of Civil Engineering

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Improving productivity in construction projects has long been a major concern, and much research has been carried out to try to ameliorate construction productivity. To this end, this study aims to improve and increase the productivity rate of flat slab formwork used in residential construction projects. A survey consisting of 150 questionnaires was undertaken to identify the factors that influence on the productivity. Based on the relative Importance Index (RII), data on eleven factors deemed to affect productivity were selected. A collection of 100 data points from various sites were utilized to develop two models. Firstly, an Artificial Neural Network (ANN) model was employed, and secondly, a parametric approach was investigated. The data were divided into two sets, with 70% of the data used for training and the remaining 30% used for testing. The models’ performance was evaluated using the Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE) values. In the test phase, the artificial neural network model yielded an MSE value of 2.6610e−4 and a MAPE value of 4.9227, whereas the parametric model produced an MSE of 0.040 and a MAPE of 9.525. It was found that the artificial neural network model provided reliable prediction accuracy compared to the parametric model. However, the artificial neural network approach can be selected as a robust model in predicting and controlling the productivity rate in local construction projects by using the developed model based on the identified factors.

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Section: Questionnaire Survey Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improvement of Productivity in Buildings Construction

Dehchar,

Boudjellal,

Bouabaz

2023

Selected Scientific Papers - Journal of Civil Engineering

View full text Add to dashboard Cite

show abstract

“…It is the process of helping the team to design a cost rather than Quantity Surveyor/Estimator costing a design. The main advantages of cost management are to provide direction for project cost management during the project life cycle [7]. The project management book [8] also stated that cost management is predominantly concerned with cost of resources required to complete a project during execution stage which include the cost of tendering, construction, maintaining, and supporting results of the project.…”

Section: Introductionmentioning

confidence: 99%

Towards the Establishment of Relationship between Macroeconomic Indicators and Cost of Public Educational Buildings in Ghana

Asamoah

Baiden

Nani

2019

Journal of Engineering

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Cost of building is usually influenced by several factors; one of such is frequent changes in macroeconomic variables. The purpose of this study is to establish the need to conduct further research on the impact of changes in macroeconomic components on the cost of public educational buildings. The study adopted the qualitative research approach; purposive and snowballing techniques were used in selecting respondents. Questionnaire survey was used to obtain primary data from respondents who were Quantity Surveyors and Estimators. The questionnaires were analyzed through descriptive analysis. Secondary data was obtained through literature review. The study revealed that respondents were satisfied with cost management procedures and practices and mainly relied on cash flow, progress reporting, and project cost control methods as means of monitoring and managing project cost. Relative important index, prime rate, interest rate, and inflation were some of the macroeconomic components that professionals considered having impact on cost. The respondents also recommended further studies on the impact of macroeconomic variability on cost of public buildings.

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Robust radioactive sources research method using possibility particle filter

Tan

et al. 2021

AIP Advances

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Of growing concern for the security of many nations are numerous incidents of lost or stolen radioactive sources or materials. The detection of and search for these abnormal radioactive sources plays an important role in monitoring nuclear safety and disposal of nuclear waste. In this paper, a method for autonomously searching for radioactive sources in a flat open rectangular-shaped field through mobile platforms was proposed. In this method, by using the possibility particle filter, the search for radioactive sources was realized according to a series of radiation information measured by the mobile platform carrying a Geiger–Müller counter. According to the inverse square law and the radiation counting governed by Poisson distribution, a radioactive source localization model was constructed. Then, a mobile platform controlled by an information entropy strategy constantly moved within the search area and detected radiation at specific points. The possibility filter algorithm, implemented via the sequential Monte Carlo method, is used to update posterior probability distributions of the source parameters. The performance of the proposed search algorithm, including a comparison with a standard particle filter algorithm, is studied by simulations. The simulation experiment proves that the possibility particle filter algorithm has good robustness. The successful application of the experimental dataset collected in the simulations verifies the measurement model and theoretical consideration.

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Reviewing of the Simulation Models in Cost Management of the Construction Projects

Cited by 6 publications

References 12 publications

Improvement of Productivity in Buildings Construction

Improvement of Productivity in Buildings Construction

Towards the Establishment of Relationship between Macroeconomic Indicators and Cost of Public Educational Buildings in Ghana

Robust radioactive sources research method using possibility particle filter

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