With the continuous development of the Internet+ education concept and the rapid advancement of online, offline, and blended teaching technologies, the existing methods of evaluating students based on teachers' subjective opinions are insufficiently objective and lack a solid foundation. To improve this situation, we propose a classroom student behavior detection model based on coordinate attention and fused residual networks, along with its talent evaluation system. The classroom student behavior detection model, based on coordinate attention and fused residual networks, effectively combines the coordinate attention mechanism and residual networks. It highlights the relevant information in student image samples by effectively utilizing channel and spatial information. The talent evaluation system accumulates and analyzes classroom data through the first application terminal, forming a learning quality report that judges the quality of talent training and provides type information of talent training. Additionally, the system receives human resource information data through the second data terminal and performs employment classification based on talent information data, obtaining occupational tendency data. Therefore, this thesis will help enhance the reliability and accuracy of human resource judgment and increase the compatibility between human resources and careers.
KEYWORDS: Data modeling, Solar energy, Control systems, Data storage, Data centers, Data acquisition, Information fusion, Inspection equipment, Intelligence systems, Distributed computing
The development of distributed energy technologies has accelerated the cross-fertilization of different energy systems and has brought new challenges to the development of the energy internet and energy management. The core of current energy development is efficient energy use and low carbon environmental protection. To achieve efficient energy use, this paper analyzes the level of intelligent control of distributed energy devices based on big data feature mining technology to enhance the autonomy of individual energy supply and energy use and the synergy of the system to achieve the purpose of decentralization. However, the existing data processing work lacks data quality evaluation standards that are unified and deeply integrated with professional management, and the quality and validity of the stock and incremental basic data cannot be assessed comprehensively. To this end, we propose and build an evaluation system for intelligent control level of distributed energy equipment, and through the establishment of a data quality evaluation system to conduct comprehensive analysis and evaluation of distributed equipment basic data, we realize effective control of basic data status and make data governance work more intelligent.
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