Construction of enterprise innovation performance model using knowledge base and edge computing

The construction of technological and innovation management system of the enterprise is studied based on the knowledge base and edge computing technology. The relationship between the knowledge depth, knowledge breadth, and the innovation performance of enterprises is analyzed following the implementation of the knowledge value chain (KVC) model. The edge-cloud collaborative scheduling method is established to research the task completion efficiency on the number of technological and innovation management tasks of enterprises. Meanwhile, the comparison is made on the efficiency of the artificial bee colony (ABC) algorithm, differential ABC (DABC) algorithm, and particle swarm optimization (PSO) algorithm in task completion, and the most efficient algorithm is used in the model. The experimental results indicate that when the knowledge of enterprises widens, the knowledge base elements of enterprises for new technologies will continue to increase. Further, the analysis of the edge-cloud collaborative resource scheduling model shows that the efficiency of the ABC algorithm in task completion reduces against more enterprise technological innovation management tasks reduces. By comparing the optimization curves of the three algorithms, it is found that the DABC algorithm makes up for the shortcomings of other algorithms, and improves the accuracy and efficiency of the algorithm in the search process. Therefore, the DABC algorithm can efficiently complete multi-objective tasks in the edge-cloud collaborative model, thereby improving the efficiency of resource scheduling for enterprises. It is hoped that the proposal can further promote enterprises to establish more robust enterprise technology management systems and achieve more efficient application management of the system.

Automated summary

The construction of the enterprise's technological and innovation management system is studied using knowledge base and edge computing technology. The DABC algorithm is found to efficiently complete multi-objective tasks in the edge-cloud collaborative model, thereby improving resource scheduling efficiency for enterprises.