ArticleMaterials (Basel, Switzerland)2022
Predicting the Lateral Load Carrying Capacity of Reinforced Concrete Rectangular Columns: Gene Expression Programming.
Article in Materials (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Numerical Evaluation of Seismic Performance of RC Columns Strengthened with Stiff-Type Polyurea.Materials (Basel, Switzerland) · 2025Article
- Numerical and artificial intelligence based investigation on the development of design guidelines for pultruded GFRP RHS profiles subjected to web crippling.Scientific reports · 2024Article
- Study Effects of Gradation and Material Thermal Property of Chip Seal Aggregates in Roller Concrete Pavement Crack Healing by Image Processing and RMS.Materials (Basel, Switzerland) · 2023Article
- Recyclable Materials for Ecofriendly Technology.Materials (Basel, Switzerland) · 2022Article
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7 authors.
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Abstract
This research presents a novel approach of artificial intelligence (AI) based gene expression programming (GEP) for predicting the lateral load carrying capacity of RC rectangular columns when subjected to earthquake loading. To achieve the desired research objective, an experimental database assembled by the Pacific Earthquake Engineering Research (PEER) center consisting of 250 cyclic tested samples of RC rectangular columns was employed. Seven input variables of these column samples were utilized to develop the coveted analytical models against the established capacity outputs. The selection of these input variables was based on the linear regression and cosine amplitude method. Based on the GEP modelling results, two analytical models were proposed for computing the flexural and shear capacity of RC rectangular columns. The performance of both these models was evaluated based on the four key fitness indicators, i.e., coefficient of determination (
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