Innovation and Practice of Socialized Development Models for Winter Sports in Higher Education Institutions in Heilongjiang Province Driven by Resource Advantages
Year: 2025
Type: article
Abstract: This study addresses the demand for socialized sharing of ice and snow sports resources in higher education institutions in Heilongjiang Province, proposing a "dual-core driven" development model.It constructs an intelligent resource integration platform based on the k-nearest neighbor clustering algorithm and optimizes teacher participation mechanisms using an agency incentive model.Through simulation experiments, the method is validated to significantly enhance resource sharing efficiency.The k-nearest neighbor clustering algorithm achieves 99.74% accuracy and 98.98% recall rate (converging after 30 iterations), representing a 6-percentage-point improvement over traditional methods.Under 500 concurrent users, resource sharing speed reaches 583.94 MB/s, with a peak throughput of 760.05 MB/s, marking a 31.7%improvement over cloud computing solutions.The sports resource information integration system constructed in this paper demonstrates strong transmission stability, with a resource loss rate of only 3.6% under high-concurrency scenarios (1,000 users), which is 1.4-2.6 percentage points lower than the comparison method.Case analysis shows that resource integration efficiency reaches 99.17%, with an average efficiency exceeding 98% across the five major resource categories.Empirical evidence indicates that this model effectively addresses the challenges of scattered, low-quality, and stagnant winter sports resources through technological innovation and mechanism coordination, providing a scalable path for the socialized development of winter sports in cold-region universities.
DOI: 10.70517/ijhsa464178
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4413461097