Analysis of countermeasures for improving the quality of college students’ entrepreneurship by deep learning and blockchain technology

Abstract

This study seeks to enhance the entrepreneurial quality of college students by introducing advanced technologies such as deep learning and blockchain. A student majoring in electronic information at a university is the research object. Based on the background of the Internet of Things and blockchain technology, the innovation and entrepreneurship information data platform for college students is constructed. The results show that the $\alpha$ values of students’ background, students’ professional ability, students’ practical ability, and students’ development ability are greater than 0.7. When determining the number of neurons in the hidden layer, the training error curve decreases continuously. The test error rises and then decreases when the number of neurons in the hidden layer is 10, 11, and 12. The Levenberg-Marquardt algorithm, selected as the training function, exhibits optimal performance with a training step count of 1,000 and achieves a performance score of 4.9. The actual values of the enhanced BPNN align closely with the expected values, demonstrating minimal deviation. The findings emphasize the importance for students in electronic information majors to actively engage in diverse social practices. This study serves as a valuable reference for enhancing the entrepreneurial quality of college students.