农业院校工科研究生课程“人工神经网络”改革与实践——以沈阳农业大学为例

Reform and Practice of Artificial Neural Network for Engineering Postgraduate Students in Agricultural Colleges and Universities: Taking Shenyang Agricultural University as an Example

人工神经网络作为人工智能领域的一个基础理论,已被广泛应用于作物性状识别、电网负荷预测、工程材料检测、土壤和水利等领域。在农业院校工科包括水利工程、农业工程、信息与电气工程等学院中,主修或选修“人工神经网络”的研究生日益增多。因此,有必要对课程的教学模式进行探索,满足不同专业研究生的需要。以沈阳农业大学“人工神经网络”硕士研究生课程为例,从线上线下教学有机结合、指导学生计算机应用、精心选用制作课件、主动征询学生意见持续改进等方面进行尝试,充分调动学生的学习兴趣和积极性,培养其创新意识和实践动手能力,取得的教学改革成果为高校研究生相关课程的教学改革提供了思路。

As a basic theory in the field of artificial intelligence,artificial neural network has been widely used in crop character recognition,power grid load prediction,engineering material detection,soil and water conservancy and other fields.In agricultural colleges and universities,including hydraulic engineering,agricultural engineering,information and electrical engineering,the number of postgraduate students majoring in Artificial Neural Network has been increasing.Therefore,it is necessary to explore the teaching mode of this course to meet the needs of graduate students of different majors.Taking Artificial Neural Network of Shenyang agricultural university postgraduate course as an example,from several aspects such as combining online and offline teaching,guiding students in computer application,carefully preparing courseware,asking for students’suggestions and so on to improve the quality of teaching,the reform fully mobilized students’learning interest and enthusiasm,cultivated their innovation consciousness and practice ability.The results provide reference for the teaching reform of postgraduate related courses in other universities.