Indirect questionnaire assessment method based on neural network prediction analysis model

The invention discloses an indirect questionnaire assessment method based on a neural network prediction analysis model, and relates to the field of automation. The method comprises that questionnaire related data is extracted; the extracted questionnaire related data is preprocessed to obtain real and qualified data; a BP neural network assessment model is constructed based on the real and qualified data; the model is trained to obtain a more effective and reasonable assessment model; knowledge obtained via the analysis model and professional knowledge are packaged in a decision service to execute a decision; and the decision service is used to determine the achievement degree of graduation requirements. The method of the invention is wide in coverage range, high in efficiency, and capable of autonomous analysis and decision and assessing learning results of students objectively. 本发明公开了种基于神经网络预测分析模型的问卷调查间接评估方法，涉及自动化领域，其包括：提取问卷调查相关数据；对提取的问卷调查相关数据进行预处理，获得真实且合格的数据；基于真实且合格的数据构建BP神经网络评估模型；训练模型以获得更加有效且合理的评估模型；将通过分