An Evaluation Model for the Innovation and Entrepreneurship Thinking Ability of College Students Based on Neural Network

Abstract

Mass innovation and entrepreneurship (I&E) is a national campaign in China. In this context, it is important to encourage college students to engage in I&E activities, and this calls for accurate and comprehensive evaluation of their I&E thinking ability. Therefore, this paper proposes an evaluation model for the I&E thinking ability of college students based on neural network (NN). Firstly, a reasonable evaluation index system was created for the I&E thinking ability of college students, and the evaluation indices were preprocessed through fuzzy analytic hierarchy process (AHP). Then, a fuzzy neural network (FNN) was constructed based on GA rule optimization and the specific steps of the algorithm were given. Moreover, a few representative rules were selected by GA based on uncertain fuzzy knowledge rules, a 4-layer NN model with fuzzy inputs and outputs was established, and the evaluation flow of the I&E thinking ability of college students was proposed. Finally, the effectiveness of the proposed model was verified through experiments. The research results of this paper provide a reference for the application of NN in the field of ability evaluation.

Innovation and Entrepreneurship of College Students Based on Random Matrix Big Data Analysis Model Educational Ecological Model Optimization

“…Traditional data analysis revolves around relational database management systems. e complexity of the data processing process in the era of Big Data rises with the expansion of the data scale [1].…”

Effectiveness Analysis of Entrepreneurial Method with Computer Data Simulation

“…e lack of an evaluation system for the efficiency of entrepreneurial practices at colleges and universities is also a factor in the low percentage of college students who are entrepreneurial. As a result, colleges and universities have an urgent challenge in boosting the effectiveness of college students' entrepreneurial practices [6][7][8][9][10].…”

Construction of a model for college students' innovation and entrepreneurship quality based on artificial intelligence technology

“…Figure 5 shows the homogeneity and completeness test results of the clustering results of college students' innovation and entrepreneurship quality indicators in this paper. To further verify the indicator clustering effect of the model in this paper, the model of reference [8], the model of reference [9], the model of reference [10] and the model of reference [11] are used as comparison models, and the adjusted Rand coefficient, mutual information and Fowlkes-Mallow's index are used as comparison indicators to analyze the indicator clustering performance of the model in this paper, and the comparison models and the obtained outcomes are presented in Figure 6. The adjusted Rand coefficient describes the similarity between the distributions of two data (quality indicators), and its value ranges from -1 to +1.…”

“…During the procedure of creating the invention and entrepreneurship quality model, Duan creatively divided the innovation and entrepreneurship process into seven stages and built a new innovation and entrepreneurship quality model. Then a system of innovation and entrepreneurship quality evaluation indexes containing 7 secondary and 21 tertiary indicators was constructed, which can objectively and systematically reveal the growth logic of innovation [10]. The evaluation method used in constructing this model lacks relevance and personalization, which leads to the lack of fairness and predictability of the final evaluation results of college students' innovation and entrepreneurship quality.…”