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Predicting pectin performance strength using near‐infrared spectroscopic data: A comparative evaluation of 1‐D convolutional neural network, partial least squares, and ridge regression modeling
Research article (Journal of Chemometrics, 2021) · cited 21× · AI/ML
Predicting pectin performance strength using near‐infrared spectroscopic data: A comparative evaluation of 1‐D convolutional neural network, partial least squares, and ridge regression modeling
Summary
Predicting pectin performance strength using near‐infrared spectroscopic data: A comparative evaluation of 1‐D convolutional neural network, partial least squares, and ridge regression modeling is a scholarly article[1].
Key Facts
Predicting pectin performance strength using near‐infrared spectroscopic data: A comparative evaluation of 1‐D convolutional neural network, partial least squares, and ridge regression modeling's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Predicting pectin performance strength using near‐infrared spectroscopic data: A comparative evaluation of 1‐D convolutional neural network, partial least squares, and ridge regression modeling. Retrieved May 24, 2026, from https://4ort.xyz/entity/predicting-pectin-performance-strength-using-nearinfrared-spectroscopic-data-a-comparative-evaluation-of-1d-convolutiona
MLA“Predicting pectin performance strength using near‐infrared spectroscopic data: A comparative evaluation of 1‐D convolutional neural network, partial least squares, and ridge regression modeling.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/predicting-pectin-performance-strength-using-nearinfrared-spectroscopic-data-a-comparative-evaluation-of-1d-convolutiona.
BibTeX@misc{4ortxyz_predicting-pectin-performance-strength-using-nearinfrared-spectroscopic-data-a-comparative-evaluation-of-1d-convolutiona_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Predicting pectin performance strength using near‐infrared spectroscopic data: A comparative evaluation of 1‐D convolutional neural network, partial least squares, and ridge regression modeling}}, year = {2026}, url = {https://4ort.xyz/entity/predicting-pectin-performance-strength-using-nearinfrared-spectroscopic-data-a-comparative-evaluation-of-1d-convolutiona}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Predicting pectin performance strength using near‐infrared spectroscopic data: A comparative evaluation of 1‐D convolutional neural network, partial least squares, and ridge regression modeling — https://4ort.xyz/entity/predicting-pectin-performance-strength-using-nearinfrared-spectroscopic-data-a-comparative-evaluation-of-1d-convolutiona (retrieved 2026-05-24)
