Optimization and Simulation of Manuscript Management System Based on Fuzzy Genetic Neural Network

Manuscript management plays an important role in the whole periodical industry. Journals and magazine society receive different types of contribution documents from all over the world. Many submission files are mostly transmitted by e-mail, but there are some hidden disadvantages in e-mail. In view...

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Bibliographic Details
Published in:Computational intelligence and neuroscience 2021, Vol.2021 (1), p.3155765-3155765
Main Author: Sun, Yongtai
Format: Article
Language:English
Subjects:
Algorithms
Artificial neural networks
Computer Simulation
Editing
Efficiency
Electronic mail
Fuzzy Logic
Learning
Neural networks
Neural Networks, Computer
Optimization
Simulation
Structured data
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Summary:Manuscript management plays an important role in the whole periodical industry. Journals and magazine society receive different types of contribution documents from all over the world. Many submission files are mostly transmitted by e-mail, but there are some hidden disadvantages in e-mail. In view of this situation, this paper studies the establishment and optimization simulation of manuscript management system based on fuzzy genetic neural network (FGNN). On the basis of genetic neural network, combined with the advantages of FNN neural network algorithm, a FGNN structure is established to optimize the system, which is helpful to the learning and expression ability of the whole system. The results show that the FGNN can extract and express the structured data, and the submission management system runs faster. Then, UML modeling and PHP framework are used to realize the design and establishment of the system, and the simulation model of contribution system is constructed. The innovation of this study is to combine genetic neural network with FNN neural network, which can query, manage, and classify manuscripts quickly. It also improves the complex submission system and optimizes the submission process. The whole journal editing work has been effectively improved.
ISSN:1687-5265
1687-5273
DOI:10.1155/2021/3155765