Study on Talent Cultivation Management Model of Universities Based on Fuzzy Neural Network Algorithm

Abstract

The Talent Cultivation Management Model for Universities represents a strategic framework designed to optimize the development and oversight of academic programs. This model focuses on identifying, nurturing, and assessing talents within the university ecosystem. It incorporates innovative methodologies to align educational offerings with individual needs and career goals. This study presents an innovative approach to developing a talent cultivation management model for universities, leveraging the integration of the Fuzzy Neural Network Algorithm with the proposed Optimized Spider Monkey Fuzzy Neural Network (OSMF-NN). Recognizing the critical importance of talent development in higher education, this research seeks to enhance the efficacy and adaptability of existing management models. The OSMF-NN algorithm, inspired by the optimization capabilities of spider monkey behavior, enhances the traditional fuzzy neural network algorithm, enabling more precise and efficient talent management. By harnessing the synergies between fuzzy logic and neural networks, the proposed model offers a robust framework for identifying, nurturing, and evaluating talents within the university ecosystem. Through comprehensive experimentation and validation, this study demonstrates the effectiveness of the OSMF-NN algorithm in optimizing talent cultivation strategies, promoting personalized learning experiences, and fostering student success in higher education institutions.