Artificial Neural Networks in Construction Engineering and Management

@inproceedings{Waziri2017ArtificialNN,
  title={Artificial Neural Networks in Construction Engineering and Management},
  author={Baba Shehu Waziri and Kabir Bala and Shehu Ahmadu Bustani},
  year={2017}
}
Artificial Neural Networks has gained considerable application in construction engineering and management in recent time. Over 100 resources published in refereed journals and conference proceedings were screened and reviewed with the view to exploring the trend and new directions of the applications of different ANN algorithms. The study revealed successful applications of ANNs in cost prediction, optimization and scheduling, risk assessment, claims and dispute resolution outcomes and decision… Expand
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References

SHOWING 1-10 OF 105 REFERENCES
Construction Engineering Cost Evaluation Model and Application Based on RS-IPSO-BP Neural Network
TLDR
A new model of construction engineering cost evaluation of optimized particle swarm and BP neural network on the basis of rough set theory is put forward, which enjoys a high practical value as it can be applied to make scientific evaluation of costs of construction Engineering. Expand
Integration of Fuzzy Logic, Particle Swarm Optimization and Neural Networks in Quality Assessment of Construction Project
The current paper presents an approach that integrates soft-computing techniques in order to facilitate the computer-aided quality assessment of construction project . W e confirmed the weight ofExpand
Neural Networks in Civil Engineering: 1989–2000
The first journal article on neural network application in civil/structural engineering was published by in this journal in 1989. This article reviews neural network articles published in archivalExpand
Application of a PSO-based neural network in analysis of outcomes of construction claims
It is generally acknowledged that construction claims are highly complicated and are interrelated with a multitude of factors. It will be advantageous if the parties to a dispute have some insightsExpand
A neural network model for decision making With application in construction management
In this paper, an innovative approach is presented to decision making using self-organiz­ ing multi-layered neural networks. The model helps make a decision whether to use a conven­ tionalExpand
Models Optimized using Swarm Intelligence Algorithms
Artificial Neural Network (ANN) has found widespread application in the field of classification. Many domains have benefited with the use of ANN based models over traditional statistical models forExpand
Application of Genetic Algorithm and Neural Network in Construction Cost Estimate
TLDR
The genetic algorithm optimizing BP has been proposed to aim at handling locality minimum and low convergence speed, and the GABP model has been built up to improve the ability of BP. Expand
Hybrid Models of Neural Networks and Genetic Algorithms for Predicting Preliminary Cost Estimates
TLDR
The research revealed that optimizing each parameter of back-propagation networks using GAs is most effective in estimating the preliminary costs of residential buildings, and GAs may help estimators overcome the problem of the lack of adequate rules for determining the parameters of NNs. Expand
Evolutionary Fuzzy Hybrid Neural Network for Conceptual Cost Estimates in Construction Projects
Conceptual cost estimates are important to project feasibility studies, even the final project success. The estimates provide significant information for project evaluations, engineering designs,Expand
Comparative study in the use of neural networks for order of magnitude cost estimating in construction
TLDR
The results showed that the linear regression model was more to the change of the number of the training data and that the PNN network was the most stable network among all the other estimating models as the maximum difference in MAPE percentage was only 2.46%. Expand
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