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Research on the Evaluation Method of Enterprises' Independent Innovation Ability Based on Improved BP Neural Network and DQN Algorithm

The development of enterprises has a very important influence on promoting national economic growth and improving comprehensive economic strength. This work evaluates the independent innovation ability of enterprises, analyzes the characteristics and difficulties of technological innovation of enter...

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Detalles Bibliográficos
Autores principales: Fan, Yipin, Ding, Ding, Qin, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8970940/
https://www.ncbi.nlm.nih.gov/pubmed/35371243
http://dx.doi.org/10.1155/2022/8250879
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author Fan, Yipin
Ding, Ding
Qin, Hong
author_facet Fan, Yipin
Ding, Ding
Qin, Hong
author_sort Fan, Yipin
collection PubMed
description The development of enterprises has a very important influence on promoting national economic growth and improving comprehensive economic strength. This work evaluates the independent innovation ability of enterprises, analyzes the characteristics and difficulties of technological innovation of enterprises, and proposes corresponding solutions to promote independent technological innovation of enterprises. Firstly, the characteristics of the research object are clarified, and on the basis of relevant research, the theory of technological innovation and evaluation at home and abroad is expounded. At the same time, the basic theory of the improved BP neural network and DQN algorithm is introduced, which provides a theoretical basis for the research of the thesis. Secondly, according to the characteristics of enterprise technological innovation, an index system for evaluating the technological innovation capability of enterprises is constructed. Then, according to the related theory of the improved BP neural network and DQN algorithm, a neural network model for evaluating the technological innovation capability of enterprises is designed, and the validity of the model is verified through empirical research. Finally, this paper applies the evaluation model to the surveyed enterprises, comprehensively analyzes the characteristics and existing problems of independent technological innovation of enterprises, and proposes practical and feasible countermeasures to improve technological innovation capabilities from the perspective of enterprises themselves. The research results of this paper can be used as an effective supplement to the research on independent technological innovation of enterprises, and at the same time promote the continuous improvement of independent technological innovation capabilities of enterprises.
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spelling pubmed-89709402022-04-01 Research on the Evaluation Method of Enterprises' Independent Innovation Ability Based on Improved BP Neural Network and DQN Algorithm Fan, Yipin Ding, Ding Qin, Hong Comput Intell Neurosci Research Article The development of enterprises has a very important influence on promoting national economic growth and improving comprehensive economic strength. This work evaluates the independent innovation ability of enterprises, analyzes the characteristics and difficulties of technological innovation of enterprises, and proposes corresponding solutions to promote independent technological innovation of enterprises. Firstly, the characteristics of the research object are clarified, and on the basis of relevant research, the theory of technological innovation and evaluation at home and abroad is expounded. At the same time, the basic theory of the improved BP neural network and DQN algorithm is introduced, which provides a theoretical basis for the research of the thesis. Secondly, according to the characteristics of enterprise technological innovation, an index system for evaluating the technological innovation capability of enterprises is constructed. Then, according to the related theory of the improved BP neural network and DQN algorithm, a neural network model for evaluating the technological innovation capability of enterprises is designed, and the validity of the model is verified through empirical research. Finally, this paper applies the evaluation model to the surveyed enterprises, comprehensively analyzes the characteristics and existing problems of independent technological innovation of enterprises, and proposes practical and feasible countermeasures to improve technological innovation capabilities from the perspective of enterprises themselves. The research results of this paper can be used as an effective supplement to the research on independent technological innovation of enterprises, and at the same time promote the continuous improvement of independent technological innovation capabilities of enterprises. Hindawi 2022-03-24 /pmc/articles/PMC8970940/ /pubmed/35371243 http://dx.doi.org/10.1155/2022/8250879 Text en Copyright © 2022 Yipin Fan et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Fan, Yipin
Ding, Ding
Qin, Hong
Research on the Evaluation Method of Enterprises' Independent Innovation Ability Based on Improved BP Neural Network and DQN Algorithm
title Research on the Evaluation Method of Enterprises' Independent Innovation Ability Based on Improved BP Neural Network and DQN Algorithm
title_full Research on the Evaluation Method of Enterprises' Independent Innovation Ability Based on Improved BP Neural Network and DQN Algorithm
title_fullStr Research on the Evaluation Method of Enterprises' Independent Innovation Ability Based on Improved BP Neural Network and DQN Algorithm
title_full_unstemmed Research on the Evaluation Method of Enterprises' Independent Innovation Ability Based on Improved BP Neural Network and DQN Algorithm
title_short Research on the Evaluation Method of Enterprises' Independent Innovation Ability Based on Improved BP Neural Network and DQN Algorithm
title_sort research on the evaluation method of enterprises' independent innovation ability based on improved bp neural network and dqn algorithm
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8970940/
https://www.ncbi.nlm.nih.gov/pubmed/35371243
http://dx.doi.org/10.1155/2022/8250879
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