<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The intelligent financial eco-management model is studied to help enterprises realize financial information transformation and enterprise digital transformation. Starting from the perceptron model, this paper describes the basic artificial neurons that make up the perceptron and introduces the structure and construction process of the multilayer perceptron model. To realize the optimal parameter selection of the multilayer perceptron, the basic principle of the Bayesian optimization algorithm is introduced, and the parameters of the multilayer perceptron model are optimized using this algorithm, which leads to the BOA-MLP evaluation model. The intelligent financial eco-management is explained, including the connotation, construction requirements and practical significance, and the data analysis of the intelligent financial eco-management model is carried out using the BOA-MLP evaluation model. From the smart financial eco-management model perspective, the most popular among enterprises is the capital pool model, accounting for 59.91%. From the financial level, the average percentages of A, B, C and D evaluations are 46.99%, 29.45%, 14.61% and 8.95%, respectively. The overall percentage of evaluations at grade C or above at the management level was 94.04%. This indicates that the intelligent financial, and ecological management model based on the BOA-MLP evaluation model should be based on the capital pool model, which can realize the financial, and ecological management information more effectively.</p>
</abstract>

The intelligent financial eco-management model is studied to help enterprises realize financial information transformation and enterprise digital transformation. Starting from the perceptron model, this paper describes the basic artificial neurons that make up the perceptron and introduces the structure and construction process of the multilayer perceptron model. To realize the optimal parameter selection of the multilayer perceptron, the basic principle of the Bayesian optimization algorithm is introduced, and the parameters of the multilayer perceptron model are optimized using this algorithm, which leads to the BOA-MLP evaluation model. The intelligent financial eco-management is explained, including the connotation, construction requirements and practical significance, and the data analysis of the intelligent financial eco-management model is carried out using the BOA-MLP evaluation model. From the smart financial eco-management model perspective, the most popular among enterprises is the capital pool model, accounting for 59.91%. From the financial level, the average percentages of A, B, C and D evaluations are 46.99%, 29.45%, 14.61% and 8.95%, respectively. The overall percentage of evaluations at grade C or above at the management level was 94.04%. This indicates that the intelligent financial, and ecological management model based on the BOA-MLP evaluation model should be based on the capital pool model, which can realize the financial, and ecological management information more effectively.

Intelligent financial eco-management model based on perceptron model

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Intelligent financial eco-management model based on perceptron model"}

The intelligent financial eco-management model is studied to help enterprises realize financial information transformation and enterprise digital...

Intelligent financial eco-management model based on perceptron model

Pubblicato online: 06 set 2023

Pagine: -

Ricevuto: 07 dic 2022

Accettato: 17 mar 2022

DOI: https://doi.org/10.2478/amns.2023.2.00300

Parole chiave
Perceptron model, Bayesian algorithm, BOA-MLP evaluation model, Intelligent finance

© 2023 Xiaoyan Deng, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Intelligent financial eco-management model based on perceptron model

Pubblicato online: 06 set 2023

Pagine: -

Ricevuto: 07 dic 2022

Accettato: 17 mar 2022

DOI: https://doi.org/10.2478/amns.2023.2.00300

Parole chiavePerceptron model, Bayesian algorithm, BOA-MLP evaluation model, Intelligent finance

© 2023 Xiaoyan Deng, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
Perceptron model, Bayesian algorithm, BOA-MLP evaluation model, Intelligent finance