Improvement of the Decision Support System Model for College Students' Entrepreneurship Path Planning Based on Tree Pruning Algorithm

ABSTRACT Aiming at the problems of high decision‐making difficulty and insufficient adaptability of traditional algorithms in college students' entrepreneurship path planning, this paper proposes a decision support system model for college students' entrepreneurship path planning based on an improved tree pruning algorithm. The model innovatively improves the traditional tree pruning algorithm, introduces entrepreneurial risk assessment factors, and designs a dynamic pruning strategy that combines the ability characteristics of entrepreneurs and a pruning decision mechanism for multiobjective optimization. The experimental simulation experiment utilized 963 sets of authentic university student entrepreneurship case data from 15 Chinese universities (initially collected 1000 sets, with 963 valid samples retained after data cleaning) to compare the improved algorithm with the traditional tree pruning algorithm, genetic algorithm, and particle swarm optimization algorithm. The results show that the path planning accuracy of the improved algorithm reaches 89.6%, which is 13.3 percentage points higher than the traditional tree pruning algorithm; it takes an average of 2.3 s to process 1000 sets of data, which is 1.5 s shorter than the traditional tree pruning algorithm; the prediction accuracy of entrepreneurship success rate is 85.3%, which is 12.9 percentage points higher than the traditional tree pruning algorithm. The constructed decision support system model can provide effective decision support for college students' entrepreneurial path planning and improve the scientificity and rationality of entrepreneurial path selection.