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March 14, 2026Engineering ReportsOpen Access

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

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This research aims to improve the decision support system model for college students' entrepreneurship path planning.
Improved tree pruning algorithm is developed incorporating entrepreneurial risk assessment.
Dynamic pruning strategy designed based on ability characteristics of entrepreneurs.
Comparative analysis against traditional algorithms using university student entrepreneurship case data.
Path planning accuracy increased to 89.6%, 13.3 percentage points higher than traditional methods.
Processing time reduced to an average of 2.3 seconds for 1000 data sets, 1.5 seconds faster than traditional pruning.
Entrepreneurship success rate prediction accuracy improved to 85.3%, 12.9 percentage points better than traditional tree pruning.

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A new model improves path planning accuracy by 13.3% using multiobjective optimization and decision support for college students' entrepreneurship.

Gao et al. (2026) studied this question.

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A new model improves path planning accuracy by 13.3% using multiobjective optimization and decision support for college students' entrepreneurship.