Hybrid BART-based models optimized by nature-inspired metaheuristics to predict ultimate axial capacity of CCFST columns
Summary
Hybrid BART-based models optimized by nature-inspired metaheuristics to predict ultimate axial capacity of CCFST columns is a scholarly article[1].
Key Facts
Hybrid BART-based models optimized by nature-inspired metaheuristics to predict ultimate axial capacity of CCFST columns's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Hybrid BART-based models optimized by nature-inspired metaheuristics to predict ultimate axial capacity of CCFST columns. Retrieved May 24, 2026, from https://4ort.xyz/entity/hybrid-bart-based-models-optimized-by-nature-inspired-metaheuristics-to-predict-ultimate-axial-capacity-of-ccfst-columns
MLA“Hybrid BART-based models optimized by nature-inspired metaheuristics to predict ultimate axial capacity of CCFST columns.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/hybrid-bart-based-models-optimized-by-nature-inspired-metaheuristics-to-predict-ultimate-axial-capacity-of-ccfst-columns.
BibTeX@misc{4ortxyz_hybrid-bart-based-models-optimized-by-nature-inspired-metaheuristics-to-predict-ultimate-axial-capacity-of-ccfst-columns_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Hybrid BART-based models optimized by nature-inspired metaheuristics to predict ultimate axial capacity of CCFST columns}}, year = {2026}, url = {https://4ort.xyz/entity/hybrid-bart-based-models-optimized-by-nature-inspired-metaheuristics-to-predict-ultimate-axial-capacity-of-ccfst-columns}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Hybrid BART-based models optimized by nature-inspired metaheuristics to predict ultimate axial capacity of CCFST columns — https://4ort.xyz/entity/hybrid-bart-based-models-optimized-by-nature-inspired-metaheuristics-to-predict-ultimate-axial-capacity-of-ccfst-columns (retrieved 2026-05-24)
