An Evaluation on Investment of Research Funds with a Neural Network Algorithm in “Double First-Class” Universities

An Evaluation on Investment of Research Funds with a Neural Network Algorithm in “Double First-Class” Universities

In the current context of the establishment of world-class universities and disciplines in China, this study examined the investment of research funds at universities. First, six variables were selected as evaluation indicators from the perspective of fixed assets, teaching configuration, research i...

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Main Authors: Jihong Sun, Yahui Li, Xiaoyun Zhao, Nanxing Zhang
Format: Article
Language:English
Published: Hindawi-Wiley 2020-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2020/7496126
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spelling doaj-8932756465de4ace9cd258fc1d592b5f2020-11-25T04:09:56ZengHindawi-WileyComplexity1076-27871099-05262020-01-01202010.1155/2020/74961267496126An Evaluation on Investment of Research Funds with a Neural Network Algorithm in “Double First-Class” UniversitiesJihong Sun0Yahui Li1Xiaoyun Zhao2Nanxing Zhang3China National Institute of Education Science, Beijing 100088, ChinaSchool of Economics, Qufu Normal University, Qufu 276800, ChinaSchool of Economics, Qufu Normal University, Qufu 276800, ChinaChina National Institute of Education Science, Beijing 100088, ChinaIn the current context of the establishment of world-class universities and disciplines in China, this study examined the investment of research funds at universities. First, six variables were selected as evaluation indicators from the perspective of fixed assets, teaching configuration, research instruments, and the number of books in libraries. Seventy-two universities were investigated from 2013 to 2017. Second, an evaluation system was constructed using the BP (backpropagation) neural network method and its applicability was verified. Finally, by adjusting the six indicators, the investment of university research funds could be adjusted and predicted to provide a reference for the construction of “first-class” universities and disciplines.http://dx.doi.org/10.1155/2020/7496126
collection DOAJ
language English
format Article
sources DOAJ
author Jihong Sun
Yahui Li
Xiaoyun Zhao
Nanxing Zhang
spellingShingle Jihong Sun
Yahui Li
Xiaoyun Zhao
Nanxing Zhang
An Evaluation on Investment of Research Funds with a Neural Network Algorithm in “Double First-Class” Universities
Complexity
author_facet Jihong Sun
Yahui Li
Xiaoyun Zhao
Nanxing Zhang
author_sort Jihong Sun
title An Evaluation on Investment of Research Funds with a Neural Network Algorithm in “Double First-Class” Universities
title_short An Evaluation on Investment of Research Funds with a Neural Network Algorithm in “Double First-Class” Universities
title_full An Evaluation on Investment of Research Funds with a Neural Network Algorithm in “Double First-Class” Universities
title_fullStr An Evaluation on Investment of Research Funds with a Neural Network Algorithm in “Double First-Class” Universities
title_full_unstemmed An Evaluation on Investment of Research Funds with a Neural Network Algorithm in “Double First-Class” Universities
title_sort evaluation on investment of research funds with a neural network algorithm in “double first-class” universities
publisher Hindawi-Wiley
series Complexity
issn 1076-2787
1099-0526
publishDate 2020-01-01
description In the current context of the establishment of world-class universities and disciplines in China, this study examined the investment of research funds at universities. First, six variables were selected as evaluation indicators from the perspective of fixed assets, teaching configuration, research instruments, and the number of books in libraries. Seventy-two universities were investigated from 2013 to 2017. Second, an evaluation system was constructed using the BP (backpropagation) neural network method and its applicability was verified. Finally, by adjusting the six indicators, the investment of university research funds could be adjusted and predicted to provide a reference for the construction of “first-class” universities and disciplines.
url http://dx.doi.org/10.1155/2020/7496126
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