Cultivation of students’ craftsmanship identity and ability based on the theory of directed percolation

Abstract

Abstract In this paper, data mining is performed based on the directed percolation theory influence mining algorithm, analyzing the maximum influence node mining proportion threshold and calculating the maximum eigenvalue of the non-return matrix. The convergence conditions of the iterative process of immobile points are analyzed to obtain the percolation threshold of the information dissemination process of directed percolation, and the initial vector is selected among the node-associated features to form the iterative formula to mine the maximum percolation theoretical influence. According to the results, students' focus on craftsmanship has risen significantly, and the percentage of students who consider persistent concentration spirit important has increased to 75%. The directed percolation theory's craftsmanship spirit is crucial for developing students' vocational skills and comprehensive literacy.