Broad Learning-Based Optimization and Prediction of Questionnaire Survey: Application to Mind Status of College Students

Abstract

The mind status of college students is important since it can reflect how the public opinion is going. Only with the accurate prediction, the corresponding actions can be conducted to prevent the situation from going worse. This paper focused on the data analysis using the recent developed broad learning method to obtain the learning model and then the prediction can be done. Firstly, the questionnaire related to the ideological state is designed. Secondly, the data are collected and classified using the typical questions and answers. Thirdly, for each pair of the question and the answer, the score is obtained and considered as data training of the system. Fourthly, the input and the output are selected according to the key questions and conclusions. Finally, the broad learning using flat network is employed for data analysis without deep structure. Tests show that the design using broad learning can efficiently deal with the regression problem and the learning network can be used for prediction.