Regression analysis has been the common tool used in construction productivity studies, but in recent years, neural networks have been a successful alternative to regression analysis for other problems similar to construction labor productivity modeling. However, the potential capabilities of neural networks for construction labor productivity modeling have not been examined. This paper discusses the development of multivariate productivity models for concrete pouring by regression analysis and neural networks
Artificial neural networks have been effectively used in various civil engineering fields, including...
Current research focuses on assessing productivity, cost, and delays for concrete batch plant (CBP) ...
Machine learning (ML) is a purpose technology already starting to transform the global economy and h...
Construction labor productivity is affected by several factors. Modeling of construction labor produ...
Construction labor productivity variations are the results of several factors. However most of the p...
Productivity of a project has a major impact on its cost and profitability. In spite of construction...
Productivity is described as the quantitative measure between the number of resources used and the o...
For having, both a qualitative as well as a quantitative analysis of various aspects of the topic, a...
This thesis presents a study of on-site labor productivity in building construction using the work s...
For planning purposes an accurate estimate of the productivity for insitu concreting operations is d...
Construction productivity is the main indicator of the performance of construction projects for any ...
Labor productivity in building construction has long been a focused research topic due to the high c...
Formwork installation, rebar fabrication/ installation, and concrete casting are often repetitive in...
The pre-planning phase prior to construction is crucial for ensuring an effective and efficient proj...
The factors that affect productivity are a major focus in construction. This article proposes a mach...
Artificial neural networks have been effectively used in various civil engineering fields, including...
Current research focuses on assessing productivity, cost, and delays for concrete batch plant (CBP) ...
Machine learning (ML) is a purpose technology already starting to transform the global economy and h...
Construction labor productivity is affected by several factors. Modeling of construction labor produ...
Construction labor productivity variations are the results of several factors. However most of the p...
Productivity of a project has a major impact on its cost and profitability. In spite of construction...
Productivity is described as the quantitative measure between the number of resources used and the o...
For having, both a qualitative as well as a quantitative analysis of various aspects of the topic, a...
This thesis presents a study of on-site labor productivity in building construction using the work s...
For planning purposes an accurate estimate of the productivity for insitu concreting operations is d...
Construction productivity is the main indicator of the performance of construction projects for any ...
Labor productivity in building construction has long been a focused research topic due to the high c...
Formwork installation, rebar fabrication/ installation, and concrete casting are often repetitive in...
The pre-planning phase prior to construction is crucial for ensuring an effective and efficient proj...
The factors that affect productivity are a major focus in construction. This article proposes a mach...
Artificial neural networks have been effectively used in various civil engineering fields, including...
Current research focuses on assessing productivity, cost, and delays for concrete batch plant (CBP) ...
Machine learning (ML) is a purpose technology already starting to transform the global economy and h...