Metaheuristic-Optimized Decision Tree Models Using Catch Fish and Hummingbird Algorithms for Predicting Creep Coefficients in Ultra-High-Performance Concrete

Abstract

Machine learning (

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Authors

  • Chao Wang Department of Architecture and Design, Qinhuangdao Vocational and Technical College, Qinhuangdao City, Hebei Province, 066100, China
  • Hao Wang Department of Architecture and Design, Qinhuangdao Vocational and Technical College, Qinhuangdao City, Hebei Province, 066100, China

DOI:

https://doi.org/10.31449/inf.v49i30.12146

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Published

12/21/2025

How to Cite

Wang, C., & Wang, H. (2025). Metaheuristic-Optimized Decision Tree Models Using Catch Fish and Hummingbird Algorithms for Predicting Creep Coefficients in Ultra-High-Performance Concrete. Informatica, 49(30). https://doi.org/10.31449/inf.v49i30.12146

Issue

Vol. 49 No. 30 (2025): Online-only issue

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Online-only

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