Neural Network Model for Parametric Cost Estimation of Highway Projects

Hegazy, Tarek; Ayed, Amr

doi:10.1061/(asce)0733-9364(1998)124:3(210)

Cited by 260 publications

(188 citation statements)

References 4 publications

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“…More sophisticated estimation models using ANN [18,19], fuzzy modeling [20], and simulation models [21] are proposed by many authors as being effective tools for cost estimation, but few are practiced in reality [22]. Whereas the estimation method for project overheads is more primitive due to lack of serious concerns [10].…”

Section: Technique Of Overhead Estimation In Projectmentioning

confidence: 99%

An Overhead Costs Assessment for Construction Projects at Gaza Strip

El-Sawalhi

El-Riyati

2015

AJCE

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An overhead cost of projects has significant role and influence on the performance of the construction companies.In addition, maintaining a good performance and quality of work away from possible loss. The purpose of the research is to examine the overhead costs management practice in the construction industry in the Gaza Strip. The awareness of construction companies and techniques followed by the contractors in estimating the overhead costs, affecting factors and mitigation measures was examined. A structured questionnaire supported by personal interviews was used to collect information. Sixtythree contracting companies working in the construction industry in the Gaza Strip were surveyed. The analysis shows a good awareness of the concept of overheads costs and its components. Gaza Strip Contractors follow precise practices to estimate the overheads costs. Contractors are taking several precautionary measures to minimize any risks associated with overheads costs. Factors affecting the estimation of overhead costs are including the management capacity of the company and its policy, led by the company's experience and ability to implement the project within the time frame. There are other factors related to the working environment of the project, especially the closure of commercial crossings of the Gaza.

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Section: Technique Of Overhead Estimation In Projectmentioning

confidence: 99%

An Overhead Costs Assessment for Construction Projects at Gaza Strip

El-Sawalhi

El-Riyati

2015

AJCE

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“…For the controlling parameters, research should be based on Hegazy and Ayed (1998). That is, the population size is generally determined by the size of the problem.…”

Section: Equation Captionmentioning

confidence: 99%

Interval Estimation of Construction Cost Using Case-Based Reasoning and Genetic Algorithms

Kim

2012

Journal of Asian Architecture and Building Engineering

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During a construction project, the cost of progress is the most important factor affecting the profitability of the project. It would be beneficial to the contractor to have prior knowledge concerning the cost of progress of a project. This study uses case-based reasoning (CBR) to predict the cost of progress in order to develop appropriate strategies. This study also investigates genetic algorithms (GAs) for weight generation and applies them to a real project case. To achieve the objective, quantitative data have been collected from real completed construction projects. The proposed prediction system, namely EVAS-CBR-GAs, was then performed on the identified influential variables. The results show that the presented methodology can consistently reduce errors and potentially be useful for owners and contractors in the early financial planning stage. Recognizing this need, the author has developed a comprehensive system for planning and controlling the cost of contractor progress.

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“…Several researchers have used neural networks as a tool for estimating costs for the earlier stage of project development .Hegazy T, and Amr Ayed [1] used a neural network approach to manage construction cost data and developped a parametric cost estimating for highway projects. They introduced two alternative techniques to train network's weights: simplex optimization (Excel's inherent solver function), and genetic algorithms, which is a flexible and adaptable model for estimating highways projects by using a spreadsheet simulation.…”

Section: Cost Estimation Model Based On Neural Networkmentioning

confidence: 99%

“…Practice shows that current artificial neural network models are based solely on elementals and parametric [1,4,9] models which relies on more details, complexity, design and time consuming.…”

Section: Introductionmentioning

confidence: 99%

A Cost Estimation Model for Repair Bridges Based on Artificial Neural Network

Bouabaz¹,

Hamami²

2008

American J. of Applied Sciences

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Estimating the total cost of bridges repair and maintenance with high accuracy is an important components, and points to a need for a cost estimation model. This paper focuses on the development of a more accurate estimation model for repair and maintenance of bridges in developing countries using artificial neural networks. Cost and design data for two categories of repair bridges were used for training and testing our neural network model, with only three main parameters used in estimating the total cost of repairing bridges. An accuracy of 96% was achieved.

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Neural Network Model for Parametric Cost Estimation of Highway Projects

Cited by 260 publications

References 4 publications

An Overhead Costs Assessment for Construction Projects at Gaza Strip

An Overhead Costs Assessment for Construction Projects at Gaza Strip

Interval Estimation of Construction Cost Using Case-Based Reasoning and Genetic Algorithms

A Cost Estimation Model for Repair Bridges Based on Artificial Neural Network

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