{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T16:16:48Z","timestamp":1771949808208,"version":"3.50.1"},"reference-count":47,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T00:00:00Z","timestamp":1671753600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Plan of China","award":["2019YFB1406303"],"award-info":[{"award-number":["2019YFB1406303"]}]},{"name":"National Key Research and Development Plan of China","award":["2020MSA300"],"award-info":[{"award-number":["2020MSA300"]}]},{"name":"Foundation of Chinese Society of Academic Degrees and Graduate Education","award":["2019YFB1406303"],"award-info":[{"award-number":["2019YFB1406303"]}]},{"name":"Foundation of Chinese Society of Academic Degrees and Graduate Education","award":["2020MSA300"],"award-info":[{"award-number":["2020MSA300"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>With the rapid development of higher education, the evaluation of the academic growth potential of universities has received extensive attention from scholars and educational administrators. Although the number of papers on university academic evaluation is increasing, few scholars have conducted research on the changing trend of university academic performance. Because traditional statistical methods and deep learning techniques have proven to be incapable of handling short time series data well, this paper proposes to adopt topological data analysis (TDA) to extract specified features from short time series data and then construct the model for the prediction of trend of university academic performance. The performance of the proposed method is evaluated by experiments on a real-world university academic performance dataset. By comparing the prediction results given by the Markov chain as well as SVM on the original data and TDA statistics, respectively, we demonstrate that the data generated by TDA methods can help construct very discriminative models and have a great advantage over the traditional models. In addition, this paper gives the prediction results as a reference, which provides a new perspective for the development evaluation of the academic performance of colleges and universities.<\/jats:p>","DOI":"10.3390\/e25010024","type":"journal-article","created":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T02:36:46Z","timestamp":1671763006000},"page":"24","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["University Academic Performance Development Prediction Based on TDA"],"prefix":"10.3390","volume":"25","author":[{"given":"Daohua","family":"Yu","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu","family":"Pan","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhendong","family":"Niu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China"},{"name":"School of Computing and Information, University of Pittsburgh, Pittsburgh, PA 15260, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xu","family":"Yuan","sequence":"additional","affiliation":[{"name":"Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing 314019, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huafei","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, China"},{"name":"Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing 314019, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Yu, D., Zhou, X., Pan, Y., Niu, Z., and Sun, H. 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