원문정보
초록
영어
This article counted the best performance of students entrepreneurship courses from 2005 to 2014, and took the best performance prediction of 2014 entrepreneurship course as the research object. According to the best annual performance of entrepreneurship courses from 2005 to 2014, this article established the grade prediction model of series combination of GM (1, 1) grey prediction model and BP neural network prediction model, and the established model was used to predict the best annual performance of students entrepreneurship course. Through comparing the actual value of the best annual performance of 2014 entrepreneurship course and the predicted value c by the model, this article analyzed the application of grey BP neural network prediction model in the students entrepreneurship performance prediction. The research results showed that for entrepreneurship performance prediction problem, the grey BP neural network prediction model had high prediction precision , simple application, and it can be widely used, and had more advantages than single GM (1, 1) grey prediction model and BP neural network model.
목차
1. Introduction
2. Grey BP Neural Network Model Introduction
2.1. Establishment Steps of BP Neural Network Prediction Model
2.2. Establishment Steps of GM (1, 1) Grey Prediction Model
2.3. Grey BP Neural Network Model Introduction
3. Establishment of Grey BP Neural Network Prediction Model
3.1. Processing of the Original Data
3.2. Establishment of the Training Sample
3.3. Establishment of BP Neural Network Prediction Model
4. Model Solution and Analysis
4.1. Training Performance Analysis of Grey BP Neural Network
4.2. Precision Test of Grey BP Neural Network
5. Conclusion
References