Through a set of intelligent systems, the cost management of construction projects can be seen in full view, and the cost information generated by each construction stage can be monitored online in real time. Once the cost limit is exceeded, an alarm will be issued immediately… In the intelligent control of a large-scale construction project in China, the cost engineers have realized the “cloud supervision” of the project cost through the “Dynamic Engineering Cost Management System Based on Data Mining Technology”, which not only saves time and effort, but also greatly improves the accuracy of the construction cost management, and brings considerable economic benefits for the project. It is understood that this scientific and technological achievement has been widely used in the field of construction engineering at home and abroad, and has received unanimous praise. Its developer is ZENG Ying, a well-known Construction Engineering Research Expert in China.
ZENG Ying has been deeply involved in the field of construction engineering for many years. She is well aware of the workflow and analysis key points of project cost management, and she is also well aware of its management drawbacks and technical bottlenecks. In order to break the technical limitations in project cost management, ZENG Ying introduced cutting-edge technologies such as big data, cloud computing, and artificial intelligence into the construction project cost system and finally developed “Dynamic Engineering Cost Management System Based on Data Mining Technology”, which not only solves the problems of low accuracy, complicated statistics, and difficult auditing in project cost management, improves management efficiency, but also comprehensively promotes the continuous improvement of the level of construction project cost management, and has contributed an important force to the intelligent upgrade of the construction engineering industry.
ZENG Ying said that in the field of construction engineering, project cost management is an important part of project management. With the rapid development of the construction industry, the role of project cost management in project construction has gradually become prominent, which can not only prevent the project investment from breaking through the quota, but also improve the management level of each construction stage, so that the limited resources such as human, material and financial resources can be fully utilized, and finally realize the maximum economic benefits. It is precisely because of this that project cost management has gradually become the key point to achieve the goal of reducing costs and increasing efficiency of engineering projects, and has attracted the attention of construction, construction and other related enterprises.
In fact, driven by advanced concepts and cutting-edge technologies, the cost management model and management method of construction projects at home and abroad have undergone earth-shaking changes. From the traditional static management mode dominated by pre-settlement mechanism gradually developed to the dynamic management mode with intelligent management system as the core, the project cost management level and cost control benefit have been greatly improved. In this process, “Dynamic Engineering Cost Management System Based on Data Mining Technology” stands out among many intelligent management systems with its outstanding application advantages and technical level, and has been fully recognized and praised in practical applications.
According to the feedback from cooperative enterprises, compared with other intelligent management systems, the value of the “Dynamic Engineering Cost Management System Based on Data Mining Technology” lies in the deep mining and efficient use of engineering cost data, so that the value of data can be fully utilized to improve the quality and efficiency of project cost management. The specific operation process is as follows:
First, data collection. The system adopts HTML information metadata extraction technology, which realizes the timely tracking and collection of the cost information of each construction stage of the construction project. It can automatically obtain the real-time cost data of the project as well.
Second, data processing. The system processes project cost data of different data sources and different structures through data mining technology, and completes the further processing and refining of the collected original data through data processes such as data cleaning, data integration and fusion, data transformation, and data reduction, and finally formed structured data for cost analysis.
Third, data application. Firstly, in the monitoring of key indicators, the system uses the decision tree algorithm to build a decision tree model based on the external influencing factors of the project. The information gain calculation method can identify the rationality of each influencing factor, determine the impact stage, and quantify the impact degree. In this way, the relationship between internal factors such as project location, structure type, and decoration level, and external factors such as policies, economy, technology, and society, and project cost are reflected, and the monitoring indicators of project cost are obtained, which is convenient for relevant personnel to monitor key indicators in real time; Secondly, in the early warning of cost deviation, the system can identify the cost control target threshold within the random fluctuation range of historical data with the help of fuzzy recognition algorithm, form a hierarchical threshold system, and then capture the abnormal data in a timely and accurate manner, realizing the deviation early warning of project cost; In addition, the system also has a cost deviation control module with an expert system as the core, which can analyze the cause of cost deviation and automatically correct it, and put forward scientific project cost management suggestions to assist cost engineers in cost control to ensure the smooth development of the project.
At present, the “Dynamic Engineering Cost Management System Based on Data Mining Technology” has helped a large number of construction engineering-related enterprises to alleviate the situation of ex post control of engineering cost management. Through the timely and accurate prediction, the effective control of the cost limit is realized, the unnecessary waste of resources is reduced, and reliable information guarantee is provided for the prediction and control of the project cost management, so that the comprehensive benefit of the project is significantly improved. Many industry experts have said that the system not only brings significant economic, social and environmental benefits to construction projects, but also comprehensively helps the engineering cost industry enter a new era of automation, intelligence and precision.
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