Abnormal state recognition method for online intelligent examination based on improved genetic algorithm
by Bo Yang; Hongbin Li; Huan Xie; Jianyong Zhao; Rong Zhu; Lei Zhao
International Journal of Information and Communication Technology (IJICT), Vol. 18, No. 3, 2021

Abstract: In order to overcome the defects of the traditional test monitoring scheme, this paper proposes a new method of online intelligent test abnormal state recognition based on improved genetic algorithm. This method sets the test status parameters and defines the criteria of abnormal status, collects the online test information and builds the information database. Image preprocessing is realised from two aspects of image segmentation and greyscale processing. The improved genetic algorithm is used to analyse and collect data intelligently and search image feature points to obtain abnormal feature extraction results. Match the extracted feature results with the established database information to realise the abnormal state recognition results, and start the corresponding abnormal alarm program. The experimental results show that the accuracy of the proposed method is 18.57% higher than that of the traditional method, indicating that the method has a better application prospect.

Online publication date: Mon, 10-May-2021

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