Construction and empirical analysis of python-based early warning model

Guanfang Yu

doi:10.1117/12.2686123

28 July 2023 Construction and empirical analysis of python-based early warning model

Guanfang Yu

Proceedings Volume 12756, 3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023); 127561A (2023) https://doi.org/10.1117/12.2686123
Event: 2023 3rd International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC 2023), 2023, Tangshan, China

Abstract

Data science, science and technology should be combined with practical applications. Scholars at home and abroad have developed many early warning models. Different models have different characteristics, and their scope of application, advantages and disadvantages are different. This research uses python to collect the financial data of small and mediumsized enterprises in recent years. learning models such as ridge regression, logistic regression, Lasso regression, support vector machine and decision tree model, and on this basis, use BP neural network to optimize the model. Among them, it introduces in detail the construction idea of enterprise financial early warning model based on neural network algorithm, clearly puts forward various indicators in the early warning mechanism, and implements further optimization through artificial neural network on the basis of the basic model. suggest an admission of the basic model.

Citation Download Citation

Guanfang Yu "Construction and empirical analysis of python-based early warning model", Proc. SPIE 12756, 3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023), 127561A (28 July 2023); https://doi.org/10.1117/12.2686123

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