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Evaluation scheme design of college information construction based on a combined algorithm
By controlling the benefits and drawbacks of informatization construction (IC) and development, evaluating the level of education informatization (EI) development can aid in university administration and decision-making. This work develops an evaluation method for the University Information Construc...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280409/ https://www.ncbi.nlm.nih.gov/pubmed/37346572 http://dx.doi.org/10.7717/peerj-cs.1327 |
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author | Shen, Caiyou Shi, Yingjuan Fang, Jing |
author_facet | Shen, Caiyou Shi, Yingjuan Fang, Jing |
author_sort | Shen, Caiyou |
collection | PubMed |
description | By controlling the benefits and drawbacks of informatization construction (IC) and development, evaluating the level of education informatization (EI) development can aid in university administration and decision-making. This work develops an evaluation method for the University Information Construction (UIC) based on the Analytical Hierarchy Process (AHP) and the Particle Swarm Optimization-based back-Propagation Neural Network (PSO-BPNN) algorithm to address the fuzziness issue in grade evaluation in the IC. Firstly, a set of data-driven evaluation index systems of the UIC effect is constructed with 16 second-class indicators and four first-class indicators of infrastructure, resource management, information management, and safeguard measures. The AHP method is used to determine the weight of the first-class indicators of the IC model. Secondly, from two perspectives of inertia weight and learning factor, the PSO-BPNN algorithm is designed to fit and analyze the level of UIC. The experimental findings demonstrate that the proposed model’s training impact is better, reflecting UIC’s effectiveness more accurately. |
format | Online Article Text |
id | pubmed-10280409 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102804092023-06-21 Evaluation scheme design of college information construction based on a combined algorithm Shen, Caiyou Shi, Yingjuan Fang, Jing PeerJ Comput Sci Algorithms and Analysis of Algorithms By controlling the benefits and drawbacks of informatization construction (IC) and development, evaluating the level of education informatization (EI) development can aid in university administration and decision-making. This work develops an evaluation method for the University Information Construction (UIC) based on the Analytical Hierarchy Process (AHP) and the Particle Swarm Optimization-based back-Propagation Neural Network (PSO-BPNN) algorithm to address the fuzziness issue in grade evaluation in the IC. Firstly, a set of data-driven evaluation index systems of the UIC effect is constructed with 16 second-class indicators and four first-class indicators of infrastructure, resource management, information management, and safeguard measures. The AHP method is used to determine the weight of the first-class indicators of the IC model. Secondly, from two perspectives of inertia weight and learning factor, the PSO-BPNN algorithm is designed to fit and analyze the level of UIC. The experimental findings demonstrate that the proposed model’s training impact is better, reflecting UIC’s effectiveness more accurately. PeerJ Inc. 2023-05-29 /pmc/articles/PMC10280409/ /pubmed/37346572 http://dx.doi.org/10.7717/peerj-cs.1327 Text en ©2023 Shen et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Algorithms and Analysis of Algorithms Shen, Caiyou Shi, Yingjuan Fang, Jing Evaluation scheme design of college information construction based on a combined algorithm |
title | Evaluation scheme design of college information construction based on a combined algorithm |
title_full | Evaluation scheme design of college information construction based on a combined algorithm |
title_fullStr | Evaluation scheme design of college information construction based on a combined algorithm |
title_full_unstemmed | Evaluation scheme design of college information construction based on a combined algorithm |
title_short | Evaluation scheme design of college information construction based on a combined algorithm |
title_sort | evaluation scheme design of college information construction based on a combined algorithm |
topic | Algorithms and Analysis of Algorithms |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280409/ https://www.ncbi.nlm.nih.gov/pubmed/37346572 http://dx.doi.org/10.7717/peerj-cs.1327 |
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