Abstract
Background: Currently, the function of information construction in the supervision and
management of construction project quality has become increasingly prominent and cannot be ignored
by administrative departments.
Objective: This study aimed to effectively supervise and manage engineering safety data and display
the system construction intuitively. Moreover, a method based on computer network technology was
also proposed.
Methods: K-means clustering, random forest, neural network, and other artificial intelligence algorithms
were used for data modelling. Evaluation tools, such as the classification model and regression
model, were used to evaluate the quality of the developed model, and a power engineering
monitoring system was established. The functions of engineering safety supervision and management,
data storage and query, graphical deformation display, data analysis and forecast, and report
outputs were analyzed.
Results: The mean square error of K-means was 7.74, that of the random forest was 27.5, and that
of the neural network was 4.4.
Conclusion: Neural network offered the smallest error and closest data. The establishment of the system
provides a new research platform for the supervision and management of power engineering safety.
Keywords:
Computer network technology, security supervision, data management performance, neural network error, information technology, informatization
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