원문정보
초록
영어
With the accelerate pace of the reform of higher education, Chinese higher education has been from the "elite education" to "popular education”, which brought a series of changes to the object of education, the way of education, educational purpose. While employment of students as an important measure of the effect of our country's higher education, there are more and more domestic universities have taken it to be the ultimate test goal. In this process, how to set up the course system to keep pace with the times has become a hot issue in educational research. In this paper, take salary as an important index to measure the students' employment ability, and through the method of fuzzy neural network for machine learning to construct the model of school courses, professional courses and elective courses contribution degree to employment to study the role of science and engineering courses in the science and engineering graduates employment, hoping to be able to promote the universities curriculum reform, and improve students' learning initiative.
목차
1. Introduction
2. Neural Network Algorithm
2.1. Artificial Neural Network
2.2. Characteristic
3. FNN
3.1 Fuzzy Neuron
3.2. The Combination of Neural Network and Fuzzy Technology
4. Study on the Science and Engineering Course Contribution of Employment Based on FNN
4.1 Construction of the Parameter Set
4.2 An empirical study:
7. Conclusion
References