Research on Innovation and Entrepreneurship Ability Based on Combination Evaluation Model

Tao Man
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Abstract

Under the background of "mass entrepreneurship and innovation", this paper analyzes the research status of college students' innovation and entrepreneurship education and its evaluation system, and gives the key factors and evaluation model which affect the cultivation of college students' innovation and entrepreneurship ability. Firstly, combining the subjective and objective advantages of AHP and entropy method, a combined weight model based on information entropy principle is constructed. Secondly, the genetic algorithm is used to optimize the neural network, and the evaluation model of college students' innovation and entrepreneurship ability based on genetic neural network is established, and the weight value obtained by combination weight model is used to adjust the connection weight of genetic neural network. Finally, the effectiveness of the combined evaluation model is verified by the data of innovation and entrepreneurship of college students in an application university. The research results can provide a new strategy for the evaluation of innovation and entrepreneurship ability of college students in application universities.
基于组合评价模型的创新创业能力研究
在“双创”背景下,分析了大学生创新创业教育及其评价体系的研究现状,给出了影响大学生创新创业能力培养的关键因素和评价模型。首先,结合层次分析法和熵法的主客观优势,构建了基于信息熵原理的组合权重模型;其次,利用遗传算法对神经网络进行优化,建立了基于遗传神经网络的大学生创新创业能力评价模型,并利用组合权重模型得到的权重值对遗传神经网络的连接权重进行调整。最后,以某应用型大学的大学生创新创业数据为例,验证了组合评价模型的有效性。研究结果可为应用型高校大学生创新创业能力评价提供新的策略。
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