Data Asset Management and Visualization Based on Intelligent Algorithm: Taking Power Equipment Data as An Example

Data asset management is adequate in solving the problem of data silence and data idleness for enterprises. Through intelligent algorithms such as neural network, in-depth learning and block chain, and guided by business needs, it extracts, analyzes and visualizes the existing business precipitation...

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Bibliographic Details
Main Authors: Xiaoming Xie, Yixuan Peng
Format: Article
Language:English
Published: Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek 2022-01-01
Series:Tehnički Vjesnik
Subjects:
Online Access:https://hrcak.srce.hr/file/404765
Description
Summary:Data asset management is adequate in solving the problem of data silence and data idleness for enterprises. Through intelligent algorithms such as neural network, in-depth learning and block chain, and guided by business needs, it extracts, analyzes and visualizes the existing business precipitation data, and forms scattered and disordered data into valuable information to support the development of the company, so as to activate data assets. Taking the management data of electric power equipment as an example, this paper proposes a method of fusion of multiple intelligent control algorithms. The specific modules include the fusion of heterogeneous data; feature extraction of equipment asset management data based on machine learning; intelligent control of multi-objective optimization environment based on energy consumption data; BIM data visualization based on data classification-energy extraction-neural network (SVM-CART-SAE-DNN) algorithm fusion. The algorithm can effectively improve the efficiency of equipment management and enhance the security and economy of power infrastructure through intelligent control of equipment management.
ISSN:1330-3651
1848-6339