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.
Factors contributing to construction machines, hand tools and power tools in building multistory buildings have been investigated. 212 non-fatal injuries have been analyzed in terms of identification ...of type of machine and tool used, indirect cause of injury, the way in which injury has occurred, severity, injured body parts and the role of the injured worker in the work process. Research has shown that trucks and tower cranes are the riskiest machines while circular saw, grinder and drilling machine are the riskiest mechanical tools. Wheelbarrow and hammer are the riskiest hand tools. Most of the injuries happen due to the "Incorrect realization of work operation". Operators are the most injured workers considering all types of machines except tower cranes. Severity levels are higher when machines and mechanical tools are used. Hand-arm and foot-leg are the most vulnerable body parts but body-torso and other multiple injuries are right behind. "Struck by an object", "Struck against", "Caught in, under or between", "Fall to level below" and "Excessive physical strain and exhaustion of the organism" are the most probable ways for an injury to occur while using construction machinery and tools.
Taking into consideration the significant impact of working force on the quality of realization of a construction process from the aspect of safety at work, it is essential to be familiar with the ...features of construction workers and identify their risk groups. Within the research, the analysis was carried out examining the influence of experience of workers in construction jobs at which they suffered an injury, along with the analysis of the influence of workers’ age on the occurrence of injuries. The type of works has an impact on the occurrence an injury only in the case when the works are realized by workers with less than 4 years of experience. It was determined that those types of works which require a certain level of professional training account for a smaller number of injuries compared with those types of work where “physical” work is dominant.
Construction management of projects via BIM Jovanov Aleksandra; Peško Igor; Mučenski Vladimir ...
Zbornik radova Građevinskog fakulteta (Subotica),
01/2019, Letnik:
2019, Številka:
36
Journal Article
Recenzirano
Odprti dostop
BIM (Building Information Modeling) is the construction of a digital integrated model (information) of an existing or future built environment.
Occupational injuries are a regular and following occurrence of every human activity and one of the major health and economic problems of modern society. Their consequences affect not only the ...injured worker, but also his family, work organization and society as a whole. This paper analyzes the causes of serious and fatal occupational injuries by four criteria: the activity of the employer, source of injury, cause of injury, and age of the injured person. It was concluded that, apart from certain illogicalities contained in the official statistics of the Ministry of Labor, the dominant factor causing serious and fatal occupational injuries in the Republic of Serbia is the human factor.
This paper presents estimation of the quantity of concrete and reinforcement that can be recycled for residential buildings constructed as skeleton structures. Models based on artificial ...intelligence, involving the use of Artificial Neural Networks (ANNs) and the Support Vector Machines (SVM) methods, were formed in order to estimate quantities of these materials. The results show that the application of ANNs and SVM methods is a good solution for the estimation of recycling capacity. The mean absolute percentage error (MAPE) for the selected ANNs for predicting quantity of concrete and reinforcement is 8.74 % and 12.58 %, respectively.
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