scholarly journals Performance measurement indices for simulated construction operations

2001 ◽  
Vol 28 (3) ◽  
pp. 383-393 ◽  
Author(s):  
Brenda McCabe ◽  
Simaan M AbouRizk
Keyword(s):  
Artificial Intelligence ◽  
Computer Simulation ◽  
Performance Improvement ◽  
Belief Networks ◽  
Remedial Action ◽  
Performance Indices ◽  
Construction Operations ◽  
Construction Engineering ◽  
Simulation Performance ◽  
Acceptable Range

This paper describes the development of indices useful in automating the experimentation process of a computer simulation. Simulation methodologies have been developed to model construction systems, but most of these systems require the experimentation process to be carried out manually. In achieving optimum performance, one has to repeat an exhaustive number of experiments. The indices can be used to automate this process, as they are indicators of bottlenecks in the system that can be tracked through the simulation output. They are based upon user-defined performance guidelines for the resources. Where a performance index falls outside the acceptable range, remedial action may be taken. Belief networks, a probabilistic form of artificial intelligence, were used to automate the analysis of the indices to determine the most likely causal factor of poor performance.Key words: construction engineering, computer simulation, performance indices, belief networks, performance improvement.

The State of Computer Simulation Applications in Construction

2011 ◽  
pp. 1554-1576
Author(s):  
Mohamed Marzouk
Keyword(s):  
Computer Simulation ◽  
Case Studies ◽  
Working Conditions ◽  
Construction Projects ◽  
Weather Conditions ◽  
The State ◽  
Construction Operations ◽  
Construction Engineering ◽  
Concrete Placement

Construction operations are performed under different working conditions including (but not limited to) unexpected weather conditions, equipment breakdown, delays in procurement, etc. As such, computer simulation is considered an appropriate technique for modeling the randomness of construction operations. Several construction processes and operations have been modeled utilizing computer simulation such as earthmoving, construction of bridges and tunnels, concrete placement operations, paving processes, and coordination of cranes operations. This chapter presents an overview of computer simulation efforts that have been performed in the area of construction engineering and management. Also, it presents two computer simulation applications in construction; earthmoving and construction of bridges’ decks. Comprehensive case studies are worked out to illustrate the practicality of using computer simulation in scheduling construction projects, taking into account the associated uncertainties inherited in construction operations.

The State of Computer Simulation Applications in Construction

2010 ◽  
pp. 509-534 ◽  
Author(s):  
Mohamed Marzouk
Keyword(s):  
Computer Simulation ◽  
Case Studies ◽  
Working Conditions ◽  
Construction Projects ◽  
Weather Conditions ◽  
The State ◽  
Construction Operations ◽  
Construction Engineering ◽  
Concrete Placement

Construction operations are performed under different working conditions including (but not limited to) unexpected weather conditions, equipment breakdown, delays in procurement, etc. As such, computer simulation is considered an appropriate technique for modeling the randomness of construction operations. Several construction processes and operations have been modeled utilizing computer simulation such as earthmoving, construction of bridges and tunnels, concrete placement operations, paving processes, and coordination of cranes operations. This chapter presents an overview of computer simulation efforts that have been performed in the area of construction engineering and management. Also, it presents two computer simulation applications in construction; earthmoving and construction of bridges’ decks. Comprehensive case studies are worked out to illustrate the practicality of using computer simulation in scheduling construction projects, taking into account the associated uncertainties inherited in construction operations.

Initial Remedial Action to Coronavirus in India: a Study

2020 ◽  
Vol 16 ◽  
Author(s):  
Pooja ◽  
Karan Veer
Keyword(s):  
Artificial Intelligence ◽  
Developing Country ◽  
Crucial Role ◽  
Essential Role ◽  
Remedial Action ◽  
Indian States

Abstract:: Because of this pandemic COVID19 (now called SARS-CoV-2), few Indian states are now at the borderline to join the transmitting stage of the virus. The condition is troubling and new scientific, environmental and infrastructure needs to play a crucial role in removing this important problem globally (including India). It focused in this report on how India; a developing country is trying to stop corona spreading, and how artificial intelligence (AI) plays an essential role in controlling and monitoring the disease. The study also focuses on the topic and the challenges a developing country such as India faces.

Development of migrant workers in construction based on machine learning and artificial intelligence technology

2020 ◽  
pp. 1-12
Author(s):  
Chen Guang
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Labor Force ◽  
Migrant Workers ◽  
Engineering Industry ◽  
Agricultural Industry ◽  
Construction Engineering ◽  
Artificial Intelligence Technology ◽  
Chinese Labor ◽  
The Times

Artificial intelligence technology has been widely used in all aspects of our life. Similarly, the application of artificial intelligence in the field of construction engineering is a necessary trend in the development of engineering industry, especially in the traditional construction engineering department. Under the background of the times, from the perspective of knowledge, artificial intelligence technology has appeared a huge development, which may have an impact on the employment of Chinese labor force, may create new jobs, or replace traditional jobs. This effect on employment is essential. From the perspective of machine learning and artificial intelligence, this paper reviews the transformation prospects of engineering industry and the development of agricultural industry in construction industry, and examines the intellectual transformation of individual human capital in Chinese labor force.

Artificial Intelligence in Construction Engineering and Management

2021 ◽  
Author(s):  
Limao Zhang ◽  
Yue Pan ◽  
Xianguo Wu ◽  
Mirosław J. Skibniewski
Keyword(s):  
Artificial Intelligence ◽  
Construction Engineering

Decision support or autonomous artificial intelligence? The case of wrong blood in tube errors

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Christopher-John L. Farrell
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Artificial Neural Network ◽  
Computer Simulation ◽  
Clinical Chemistry ◽  
Human Interaction ◽  
Final Decision ◽  
P Values ◽  
Laboratory Staff

Abstract Objectives Artificial intelligence (AI) models are increasingly being developed for clinical chemistry applications, however, it is not understood whether human interaction with the models, which may occur once they are implemented, improves or worsens their performance. This study examined the effect of human supervision on an artificial neural network trained to identify wrong blood in tube (WBIT) errors. Methods De-identified patient data for current and previous (within seven days) electrolytes, urea and creatinine (EUC) results were used in the computer simulation of WBIT errors at a rate of 50%. Laboratory staff volunteers reviewed the AI model’s predictions, and the EUC results on which they were based, before making a final decision regarding the presence or absence of a WBIT error. The performance of this approach was compared to the performance of the AI model operating without human supervision. Results Laboratory staff supervised the classification of 510 sets of EUC results. This workflow identified WBIT errors with an accuracy of 81.2%, sensitivity of 73.7% and specificity of 88.6%. However, the AI model classifying these samples autonomously was superior on all metrics (p-values<0.05), including accuracy (92.5%), sensitivity (90.6%) and specificity (94.5%). Conclusions Human interaction with AI models can significantly alter their performance. For computationally complex tasks such as WBIT error identification, best performance may be achieved by autonomously functioning AI models.

scholarly journals Corporate digital responsibility (CDR) in construction engineering—ethical guidelines for the application of digital transformation and artificial intelligence (AI) in user practice

2021 ◽  
Vol 3 (10) ◽  
Author(s):  
Bianca Weber-Lewerenz
Keyword(s):  
Artificial Intelligence ◽  
Business Models ◽  
Research Question ◽  
Transformation Process ◽  
Digital Transformation ◽  
Fundamental Rights ◽  
Ethical Framework ◽  
Ethical Guidelines ◽  
Ethical Perspective ◽  
Construction Engineering

AbstractDigitization is developing fast and has become a powerful tool for digital planning, construction and operations, for instance digital twins. Now is the right time for constructive approaches and to apply ethics-by-design in order to develop and implement a safe and efficient artificial intelligence (AI) application. So far, no study has addressed the key research question: Where can corporate digital responsibility (CDR) be allocated, and how shall an adequate ethical framework be designed to support digital innovations in order to make full use of the potentials of digitization and AI? Therefore, the research on how best practices meet their corporate responsibility in the digital transformation process and the requirements of the EU for trustworthy AI and its human-friendly use is essential. Its transformation bears a high potential for companies, is critical for success and thus, requires responsible handling. This study generates data by conducting case studies and interviewing experts as part of the qualitative method to win profound insights into applied practice. It provides an assessment of demands stated in the Sustainable Development Goals by the United Nations (SDGs), White Papers on AI by international institutions, European Commission and German Government requesting the consideration and protection of values and fundamental rights, the careful demarcation between machine (artificial) and human intelligence and the careful use of such technologies. The study discusses digitization and the impacts of AI in construction engineering from an ethical perspective. This research critically evaluates opportunities and risks concerning CDR in construction industry. To the author’s knowledge, no study has set out to investigate how CDR in construction could be conceptualized, especially in relation to digitization and AI, to mitigate digital transformation both in large, medium- and small-sized companies. This study applies a holistic, interdisciplinary, inclusive approach to provide guidelines for orientation and examine benefits as well as risks of AI. Furthermore, the goal is to define ethical principles which are key for success, resource-cost-time efficiency and sustainability using digital technologies and AI in construction engineering to enhance digital transformation. This study concludes that innovative corporate organizations starting new business models are more likely to succeed than those dominated by a more conservative, traditional attitude.

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