Analysis of talent cultivation path based on elastic regression network algorithm for recreation tourism industry in the context of industry-education integration

Abstract

Abstract In this paper, according to the elastic regression network algorithm model, the evaluation attribute values are normalized, the variables are analyzed by multiple regression, and the weights of evaluation attributes are calculated using the entropy weight method. Then, the talent demand of the recreation tourism industry is studied, and the talent training model of industry-education integration in the recreation tourism industry is constructed. Finally, the analysis of talent cultivation identity, satisfaction, and results was conducted using the elastic regression network. The results show that the average score of students’ self-appraisal of cultivation results reached 4.76, and the average score of enterprise evaluation was 4.28. The teachers’ identity rating of teaching management is 4, and the student’s identity rating is 4.616. The teachers’ identity rating of school-enterprise cooperation is 3.79, and the student’s identity rating is 4.465. This paper’s research aims to promote the recreation and tourism industry’s development and enhance talent training quality.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 3 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.