Comprehensive Evaluation of BIM Calculation Quantity in Domestic Construction Engineering Based on Fuzzy Comprehensive Evaluation

Nowadays, with the leap-forward development of computer technology and the transformation of information technology management concepts, China’s construction industry is quietly entering the era of refined management. Accurate estimation and cost control have become among the key considerations of the construction industry. For the calculation of engineering quantity, there are already many software devices that can be used for the calculation of engineering structure quantity, which means that the incorrect operation of personnel has been reduced to some extent, improving the work efficiency and measurement accuracy. The purpose of this paper is to solve the problems of computational missing, computational errors, inefficiency, data loss, and repetitive system in traditional computing based on the advantages of BIM computing system, which provide a reliable basis for cost forecasting and control. At the same time, using BMI calculation system to solve the problem of steel reinforcement in construction engineering, as well as the use of personnel, the existing calculation software still needs a lot of time and energy. We proposed a comprehensive evaluation study of reinforcement calculation in domestic construction engineering BIM calculation system based on a fuzzy comprehensive evaluation. This paper first summarizes the BIM calculation system of construction engineering, uses fuzzy comprehensive evaluation system as an important evaluation index system in domestic construction engineering BIM calculation system, through the judgment of various factors affecting the actual effect of the calculation system, and uses the fuzzy evaluation system combined with a case to demonstrate the superiority of the proposed research. Therefore, through the above research and experiments, it is concluded that the research method of this paper solves many problems in the process of engineering structure reinforcement calculation and provides a good reference method for the establishment of comprehensive evaluation system of reinforcement calculation, as well as providing an effective validation for the widespread use of BIM technology in the construction industry. Finally, it is also beneficial for users to comprehensively evaluate the BIM calculation system of the construction industry and provide a basic reference condition for different industries to use and choose BIM calculation systems.

Investigation of parameters recorded by the monitoring system of an engineering structure using big data analysis methods

В работе представлены результаты анализа и обработки с помощью математического аппарата «науки о больших данных» информации, получаемой в системе мониторинга напряженно-деформированного состояния морского инженерного сооружения. Для анализа данных использована процедура машинного обучения с учителем, рассмотрены различные модели машинного обучения. Приведен пример анализа результатов работы системы мониторинга напряженно-деформированного состояния морской нефтедобывающей платформы. Предложены варианты оптимизации системы путем уменьшения числа рассматриваемых датчиков и замены их математической моделью. Созданы математические модели для восстановления значений специально исключенных датчиков, а также для построения краткосрочного и долгосрочного прогнозов. С помощью анализа больших данных получена новая информация пригодная для практических и научных целей. The paper presents the results of analysis and processing with the help of the mathematical apparatus of the "science of big data" of information received in the monitoring system of the stress-strain state of a marine engineering structure. For data analysis, the machine learning procedure with a teacher is used, various machine learning models are considered. An example of the analysis of the results of the monitoring system of the stress-strain state of an offshore oil production platform is given. Options for optimizing the system are proposed - reducing the number of sensors under consideration. Mathematical models have been created to restore the values of specially excluded sensors, as well as to build short-and long-term forecasts. With the help of big data analysis, new information has been obtained that is suitable for practical and scientific purposes.