scholarly journals Smart optimization for mega construction projects using artificial intelligence

2014 ◽  
Vol 53 (3) ◽  
pp. 591-606 ◽  
Author(s):  
Remon Fayek Aziz ◽  
Sherif Mohamed Hafez ◽  
Yasser Ragab Abuel-Magd
Keyword(s):  
Artificial Intelligence ◽  
Construction Projects

scholarly journals Use of artificial intelligence for estimating cost of integral bridges

2021 ◽  
Vol 73 (03) ◽  
pp. 265-273
Author(s):  
Stjepan Lakusic
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Cost Estimation ◽  
Construction Projects ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Estimation Model ◽  
Construction Costs ◽  
The Mean ◽  
Early Phases

Estimation of costs is important in every phase of realisation of construction projects. However, the influence of cost estimation is the highest in early phases as it is then that the decision about accepting the job or withdrawing from the project is made. The quantity of data available in initial phases of the project is smaller compared to subsequent phases, which affects accuracy of cost estimation in such early phases. A research making use of artificial intelligence to estimate construction costs of integral road bridges is presented in the paper. The estimation model is prepared by means of neural networks. The best neural network model has proven to be highly accurate in the estimation of costs based on the mean absolute error, which amounts to 13.40 %.

scholarly journals Potentials of artificial intelligence in construction management

2020 ◽  
Vol 12 (1) ◽  
pp. 2053-2063
Author(s):  
Wolfgang Eber
Keyword(s):  
Artificial Intelligence ◽  
Construction Management ◽  
Construction Projects ◽  
Information Technologies ◽  
Hierarchical Control ◽  
Human Mind ◽  
High Degree ◽  
The Given ◽  
Creative Construction

AbstractArtificial intelligence (AI) approaches have been developed since the upcoming of Information Technologies beginning in the 1950s. With rising computing power, the discussion of AI usefulness has been refuelled by new powerful algorithms and, in particular, the availability of the internet as a vast resource of unstructured data.This gives hope to construction management in particular, since construction projects are recently becoming larger and more complex, i.e. encompassing more and more participants focusing on diverging interests while the given frames of time and budget are getting tighter. Finally, construction management is used to establish an efficient organisation of all these issues and able to predict the result with a high degree of precision and certainty.This could be accomplished by the human mind when projects were smaller, but with the recent development human mind is clearly pushed to its limits. On this background, the possible support of AI to organisational tasks needs to be investigated on a theoretical level prior to developing tools. This paper is the extended version of the article ‘Artificial Intelligence in Construction Management – a Perspective’, presented at the Creative Construction Conference 2019 where the algorithmic and entropic scope of AI is investigated in the context of construction management. However, efficient organisation is about restructuring systems into a set of well-separated subsystems, where human intelligence is required to bring in mainly two higher principles which AI fails to provide: the ability to prioritise and creativity allowing for new approaches not derived from given data.This paper additionally focuses on the aspect of in-situ coordination. This service is an aspect of organisation which is not separable and can therefore only be treated as self-determined subsystem, located outside of hierarchical control. At this point algorithms of AI need to be investigated not so much as to substitute human mind but to provide significant support.

scholarly journals Estimation of Costs and Durations of Construction of Urban Roads Using ANN and SVM

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Igor Peško ◽  
Vladimir Mučenski ◽  
Miloš Šešlija ◽  
Nebojša Radović ◽  
Aleksandra Vujkov ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Support Vector Machines ◽  
Construction Projects ◽  
Percentage Error ◽  
Support Vector ◽  
Building Process ◽  
Vector Machines ◽  
Specific Part

Offer preparation has always been a specific part of a building process which has significant impact on company business. Due to the fact that income greatly depends on offer’s precision and the balance between planned costs, both direct and overheads, and wished profit, it is necessary to prepare a precise offer within required time and available resources which are always insufficient. The paper presents a research of precision that can be achieved while using artificial intelligence for estimation of cost and duration in construction projects. Both artificial neural networks (ANNs) and support vector machines (SVM) are analysed and compared. The best SVM has shown higher precision, when estimating costs, with mean absolute percentage error (MAPE) of 7.06% compared to the most precise ANNs which has achieved precision of 25.38%. Estimation of works duration has proved to be more difficult. The best MAPEs were 22.77% and 26.26% for SVM and ANN, respectively.

scholarly journals Applied artificial intelligence for predicting construction projects delay

2021 ◽  
Vol 6 ◽  
pp. 100166
Author(s):  
Christian Nnaemeka Egwim ◽  
Hafiz Alaka ◽  
Luqman Olalekan Toriola-Coker ◽  
Habeeb Balogun ◽  
Funlade Sunmola
Keyword(s):  
Artificial Intelligence ◽  
Construction Projects ◽  
Applied Artificial Intelligence

scholarly journals APPLYING METAHEURISTIC STRATEGIES IN CONSTRUCTION PROJECTS MANAGEMENT

2012 ◽  
Vol 18 (5) ◽  
pp. 621-630 ◽  
Author(s):  
Wojciech Boejko ◽  
Zdzisław Hejducki ◽  
Mieczysław Wodecki
Keyword(s):  
Artificial Intelligence ◽  
Construction Projects ◽  
Search Algorithm ◽  
Scatter Search ◽  
Industrial Building ◽  
Real Analysis ◽  
The Real ◽  
Scatter Search Algorithm ◽  
Building Project ◽  
Project Realization

This work deals with the application of artificial intelligence instruments in a building schedule. In this article there was presented an original optimization scatter search algorithm taking into consideration both technological and organizational restrictions. This algorithm was applied to the real analysis of the industrial building project realization.

A THEORETICAL EVALUATION ON THE IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE FOR LEARNING CURVE FOR BUILT ENVIRONMENT

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Mokgaetji Gift ◽  
Xolile Nokulunga
Keyword(s):  
Artificial Intelligence ◽  
Construction Industry ◽  
Construction Projects ◽  
Empirical Studies ◽  
Development Stage ◽  
The Body ◽  
Structured Interviews ◽  
Theoretical Evaluation ◽  
Increase Productivity ◽  
And Performance

Artificial Intelligence (AI) technology has the power to unlock the challenges faced in construction projects such as poor efficiency issues, design errors, low productivity, and accidents on site. Therefore, the study is a literature review on the evaluation of the implementation of AI technology on South African construction projects. The method adopted in this study is based on the cross analyses of inferences from structured interviews with reference to existing theoretical literature, published and unpublished research. The primary findings emanating from this study reveals that past other underground empirical studies have identified several important impacts of AI technology and how it can revolutionize the construction industry. This includes timely delivery of the projects, improved profitability, and reduced construction errors. Moreover, the study revealed that if AI technology is fully exposed and exploited on construction projects especially to both developed and developing countries it would certainly eliminate design errors, increase productivity, improve efficiency, and performance issues. However, the adoption of AI technology in South Africa is still at an early development stage. The study would contribute to the body of existing knowledge of AI technology. Again, it will help construction industry professionals to advance their workplaces and organizations.

scholarly journals Cost Forecasting of Public Construction Projects Using Multilayer Perceptron Artificial Neural Networks: A Case Study

2021 ◽  
Vol 41 (3) ◽  
pp. e87737
Author(s):  
Alcineide Pessoa ◽  
Gean Sousa ◽  
Luiz Maués ◽  
Felipe Alvarenga ◽  
Débora Santos
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Public Sector ◽  
Multilayer Perceptron ◽  
Construction Projects ◽  
Gradient Descent Method ◽  
The Neural Network ◽  
Artificial Neural

The execution of public sector construction projects often requires the use of financial resources not foreseen during the tendering phase, which causes management problems. This study aims to present a computational model based on artificial intelligence, specifically on artificial neural networks, capable of forecasting the execution cost of construction projects for Brazilian educational public buildings. The database used in the training and testing of the neural model was obtained from the online system of the Ministry of Education. The neural network used was a multilayer perceptron as a backpropagation algorithm optimized through the gradient descent method. To evaluate the obtained results, the mean absolute percentage errors and the Pearson correlation coefficients were calculated. Some hypothesis tests were also carried out in order to verify the existence of significant differences between real values and those obtained by the neural network. The average percentage errors between predicted and actual values varied between 5% and 9%, and the correlation values reached 0,99. The results demonstrated that it is possible to use artificial intelligence as an auxiliary mechanism to plan construction projects, especially in the public sector.

scholarly journals Prediction of Risk Delay in Construction Projects Using a Hybrid Artificial Intelligence Model

2020 ◽  
Vol 12 (4) ◽  
pp. 1514 ◽  
Author(s):  
Zaher Mundher Yaseen ◽  
Zainab Hasan Ali ◽  
Sinan Q. Salih ◽  
Nadhir Al-Ansari
Keyword(s):  
Artificial Intelligence ◽  
Construction Projects ◽  
Performance Measure ◽  
Classification Error ◽  
Construction Project Management ◽  
Algorithm Optimization ◽  
Reliable Technique ◽  
Hybrid Artificial Intelligence ◽  
The Impact ◽  
Delay Prediction

Project delays are the major problems tackled by the construction sector owing to the associated complexity and uncertainty in the construction activities. Artificial Intelligence (AI) models have evidenced their capacity to solve dynamic, uncertain and complex tasks. The aim of this current study is to develop a hybrid artificial intelligence model called integrative Random Forest classifier with Genetic Algorithm optimization (RF-GA) for delay problem prediction. At first, related sources and factors of delay problems are identified. A questionnaire is adopted to quantify the impact of delay sources on project performance. The developed hybrid model is trained using the collected data of the previous construction projects. The proposed RF-GA is validated against the classical version of an RF model using statistical performance measure indices. The achieved results of the developed hybrid RF-GA model revealed a good resultant performance in terms of accuracy, kappa and classification error. Based on the measured accuracy, kappa and classification error, RF-GA attained 91.67%, 87% and 8.33%, respectively. Overall, the proposed methodology indicated a robust and reliable technique for project delay prediction that is contributing to the construction project management monitoring and sustainability.

scholarly journals Construction Cost Simulation Based on Artificial Intelligence and BIM

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xingliang Du
Keyword(s):  
Artificial Intelligence ◽  
Construction Projects ◽  
Early Stage ◽  
Project Cost ◽  
Construction Engineering ◽  
Artificial Intelligence Technology ◽  
Cost Simulation ◽  
Construction Project Cost ◽  
The Cost ◽  
Engineering Cost

Quickly estimating the main engineering quantity and project cost of the project is conducive to the management staff to have an overall grasp of the project in the early stage and to grasp the development direction of the project in advance. Moreover, it can play an important guiding role in the further construction management of the project and can help managers prevent the emergence of unfavorable factors in the project, make corresponding construction deployments, and avoid risks. This paper combines artificial intelligence technology to construct a construction project cost simulation system. In this system, BIM is mainly used to simulate construction engineering, and the construction engineering cost is simulated and analyzed in combination with the pricing file. Finally, the results of experimental research show that the intelligent model proposed in this paper can play an important role in the cost of construction projects.

scholarly journals Implementation of artificial intelligence in the construction industry and analysis of existing technologies

2021 ◽  
Vol 2 (2(58)) ◽  
pp. 12-15
Author(s):  
Kateryna Kyivska ◽  
Svitlana Tsiutsiura
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Information Technology ◽  
Fuzzy Logic ◽  
Construction Industry ◽  
Construction Projects ◽  
Machine Learning Algorithms ◽  
Learning Technology ◽  
Time Data ◽  
Knowledge Based

The object of research is the process of using information technology in the construction industry. One of the most problematic areas is increasing the efficiency of the construction industry through the introduction of digital technologies. The research carried out is based on the application of an approach that is implemented using artificial intelligence. The study used machine learning and fuzzy logic methods to mark visual data and analyze it for potential threats, as well as to reduce all possible risks. The main feature of this approach is that using machine learning technology, it is possible to reduce the risks of a project before they affect its profit. So, using artificial intelligence in combination with BIM technologies, it is possible to predict work on construction projects based on real-time data, past activities and other factors in such a way as to optimize construction processes. The benefits to be gained from implementing digital processes will become even more evident in future projects as AI continues to analyze company data. This is due to the fact that the proposed approach using fuzzy logic has a number of features, in particular, the more information machine learning algorithms process, the more complex they become. As a result, they provide even more useful information and allow to make even better decisions. This provides an opportunity to minimize risks and efficiently allocate resources when working on projects. Compared to conventional information technology, artificial intelligence can be used to build a knowledge-based security management system and combine statistical probabilities to help mitigate security risks in construction projects.

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