scholarly journals Evaluation of College Students' Innovation and Entrepreneurial Ability for the Science and Technology Service Industry

2021 ◽  
Vol 16 (05) ◽  
pp. 228
Author(s):  
Yanming Qi ◽  
Tong Liang ◽  
Yongzhi Chang
Keyword(s):  
College Students ◽  
Structural Equation ◽  
Service Industry ◽  
Evaluation Model ◽  
Science And Technology ◽  
Evaluation Index System ◽  
Likelihood Method ◽  
Analysis Model ◽  
Technology Service ◽  
Entrepreneurial Ability

The development level of the science and technology service industry is an important factor affecting the development speed of regional economy and the formation of innovation ability and development potential of the region, and the construction of talent team is the core and foundation for the development of the science and technology service industry. To measure such ability, this paper constructed an evaluation model for the innovation and entrepreneurial ability (IEA) of college students. First, a corresponding evaluation index system was established, the quantifiable index data were subject to factor analysis, and the structural equation model was subject to regression estimation using the maximum likelihood method. Then, from multiple aspects such as the level of the colleges, the major of the students, and the gender of the students, this paper comprehensively analyzed college students’ IEA. And finally, based on one-way analysis of variance, the differences between indexes were analyzed, and a path analysis model was established to analyze the relationship between the science and technology service industry’s regional industrial scale, resource input, informatization level, spatial agglomeration degree, and college students’ IEA.

scholarly journals Research on the development level of science and technology service industry under the information economy

2021 ◽  
Vol 251 ◽  
pp. 01116
Author(s):  
Jinrong Shan
Keyword(s):  
Service Industry ◽  
Science And Technology ◽  
Information Age ◽  
Evaluation Index System ◽  
Information Economy ◽  
Statistical Software ◽  
Development Level ◽  
Technology Service ◽  
Transfer Station ◽  
Depth Study

As a transfer station between economic development and technology, science and technology service industry is an important guarantee for the state to provide services under the strategy of science and technology Innovation. However, in the information age, the development of the industry will be affected by what factors need further in-depth study, this paper based on existing literature, in the original evaluation index system of the development level of science and technology service industry, the information related index is added, and 31 provinces in China are factorial analyzed by using SPSS Statistical Software, and the comprehensive scores of each province and city are calculated and ranked, in order to put forward countermeasures and suggests.

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

2021 ◽  
Vol 16 (02) ◽  
pp. 188
Author(s):  
Feng Zhang ◽  
Limin Xi
Keyword(s):  
Neural Network ◽  
College Students ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Evaluation Index System ◽  
Analytic Hierarchy ◽  
Thinking Ability ◽  
Fuzzy Neural ◽  
Knowledge Rules ◽  
Innovation And Entrepreneurship

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.

scholarly journals The evaluation of college students’ innovation and entrepreneurship ability based on nonlinear model

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Guihong Liang ◽  
Daniyal M. Alghazzawi ◽  
Nympha Rita Joseph
Keyword(s):  
College Students ◽  
Structural Model ◽  
Evaluation Model ◽  
Entrepreneurship Education ◽  
Colleges And Universities ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Ecological Environment ◽  
Index Weight ◽  
Innovation And Entrepreneurship

Abstract Under the background of ‘mass entrepreneurship and innovation’, Chinese colleges and universities have strengthened students’ entrepreneurial and innovative abilities. The article first analyses the reasons why applied universities should strengthen innovation and entrepreneurship education. On this basis, the evaluation index system of students’ innovation and entrepreneurship ability is constructed. The thesis uses the nonlinear structural model to complete the index weight setting. Finally, the paper verifies the effectiveness of the combined evaluation model through the data on innovation and entrepreneurship of college students in an university where applied. At the same time, the article proposes measures for optimising the ecological environment of innovation and entrepreneurship education for colleges and universities.

scholarly journals Quantitative Analysis of the Impact of Wireless Internet Technology on College Students’ Innovation and Entrepreneurship under the Background of “Internet Plus”

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Qinqin Lou
Keyword(s):  
College Students ◽  
Quantitative Analysis ◽  
Wireless Network ◽  
Evaluation Model ◽  
Fuzzy Optimization ◽  
Evaluation Index System ◽  
Network Technology ◽  
Proposed Model ◽  
Weight Model ◽  
Innovation And Entrepreneurship

Under the background of “Internet plus,” the opportunities and challenges that college students face in the process of innovation and entrepreneurship coexist. College students should make full use of the powerful function of the Internet to excavate the huge business opportunities hidden under the background of “Internet plus.” In the context of “Internet plus” of mass entrepreneurship and innovation, the quantitative analysis method is studied in the context of wireless network technology on college students’ innovation and entrepreneurship. This paper proposes a combined weight model and an evaluation model based on genetic fuzzy optimization neural network. This research initially establishes an evaluation index system (EIS) by analyzing the influence factors of wireless network technology on college students’ innovation and entrepreneurship. In addition, EIS is also analyzed by combining the objective weight of each index obtained by the entropy with the subjective weight of each index obtained by the analytic hierarchy process to construct a combined weight model. A genetic algorithm is used to optimize fuzzy optimization neural networks and establish an evaluation index system of wireless network technology based on genetic fuzzy optimization neural network. To minimize the output error, the function of output error is used as the fitness evaluation function to output the score after several iterations. The experimental results show that the evaluation model can determine the importance of the influencing factors of wireless network technology on college students’ innovation and entrepreneurship. It is further evident from the experiments that the proposed model has high accuracy, with the average relative error always less than 1%, which can further improve the effect of quantitative analysis. The proposed model also has a fast convergence speed that can prevent local minima.

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