<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>9</volume><submitter>Shen C</submitter><pubmed_abstract>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 weig</pubmed_abstract><journal>PeerJ. Computer science</journal><pagination>e1327</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC10280409</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Evaluation scheme design of college information construction based on a combined algorithm.</pubmed_title><pmcid>PMC10280409</pmcid><pubmed_authors>Fang J</pubmed_authors><pubmed_authors>Shen C</pubmed_authors><pubmed_authors>Shi Y</pubmed_authors></additional><is_claimable>false</is_claimable><name>Evaluation scheme design of college information construction based on a combined algorithm.</name><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 weig</description><dates><release>2023-01-01T00:00:00Z</release><publication>2023</publication><modification>2025-04-05T13:54:17.415Z</modification><creation>2025-02-19T03:56:02.129Z</creation></dates><accession>S-EPMC10280409</accession><cross_references><pubmed>37346572</pubmed><doi>10.7717/peerj-cs.1327</doi></cross_references></HashMap>