Prediction of financial performance of listed companies based on grey TOPSIS-CNN
Reasonably evaluating and predicting the financial performance of companies is very important for the sustainable and healthy development of listed companies.The paper proposes an company financial performance prediction model that inte-grates grey TOPSIS and one-dimensional convolutional neural network.The grey TOPSIS is used to do comprehensive evaluation of the corporate performance of listed companies,the labels are generated by K-mean clustering,the SMOTE algorithm is introduced to solve the problem of data imbalance,and finally the convolutional neural network is used for performance prediction.The results show that the accuracy of the model proposed in this paper reaches 96.35%,which is an average improvement of 5.76%compared with grey TOPSIS-Kmeans-SMOTE-CNN,grey TOPSIS-Kmeans-CNN,Kmeans-CNN,Kmeans-SVM,and Kmeans-KNN,and the macro-averaged performance of each evaluation index is also better.It shows that our proposed corporate financial performance classification model performs better and has positive significance for corporate financial performance management.
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