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Self-learning locally-optimal hypertuning using maximum entropy, and comparison of machine learning approaches for estimating fatigue life in composite materials of the aerospace industry
Research article (Engineering Structures, 2023) · cited 17× · AI/ML
Self-learning locally-optimal hypertuning using maximum entropy, and comparison of machine learning approaches for estimating fatigue life in composite materials of the aerospace industry
Summary
Self-learning locally-optimal hypertuning using maximum entropy, and comparison of machine learning approaches for estimating fatigue life in composite materials of the aerospace industry is a scholarly article[1].
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Self-learning locally-optimal hypertuning using maximum entropy, and comparison of machine learning approaches for estimating fatigue life in composite materials of the aerospace industry's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Self-learning locally-optimal hypertuning using maximum entropy, and comparison of machine learning approaches for estimating fatigue life in composite materials of the aerospace industry. Retrieved May 24, 2026, from https://4ort.xyz/entity/self-learning-locally-optimal-hypertuning-using-maximum-entropy-and-comparison-of-machine-learning-approaches-for-estima
MLA“Self-learning locally-optimal hypertuning using maximum entropy, and comparison of machine learning approaches for estimating fatigue life in composite materials of the aerospace industry.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/self-learning-locally-optimal-hypertuning-using-maximum-entropy-and-comparison-of-machine-learning-approaches-for-estima.
BibTeX@misc{4ortxyz_self-learning-locally-optimal-hypertuning-using-maximum-entropy-and-comparison-of-machine-learning-approaches-for-estima_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Self-learning locally-optimal hypertuning using maximum entropy, and comparison of machine learning approaches for estimating fatigue life in composite materials of the aerospace industry}}, year = {2026}, url = {https://4ort.xyz/entity/self-learning-locally-optimal-hypertuning-using-maximum-entropy-and-comparison-of-machine-learning-approaches-for-estima}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Self-learning locally-optimal hypertuning using maximum entropy, and comparison of machine learning approaches for estimating fatigue life in composite materials of the aerospace industry — https://4ort.xyz/entity/self-learning-locally-optimal-hypertuning-using-maximum-entropy-and-comparison-of-machine-learning-approaches-for-estima (retrieved 2026-05-24)
