An efficient tea quality classification algorithm based on near infrared spectroscopy and random Forest
Summary
An efficient tea quality classification algorithm based on near infrared spectroscopy and random Forest is a scholarly article[1].
Key Facts
An efficient tea quality classification algorithm based on near infrared spectroscopy and random Forest's instance of is recorded as scholarly article[2].
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). An efficient tea quality classification algorithm based on near infrared spectroscopy and random Forest. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-efficient-tea-quality-classification-algorithm-based-on-near-infrared-spectroscopy-and-random-forest
MLA“An efficient tea quality classification algorithm based on near infrared spectroscopy and random Forest.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-efficient-tea-quality-classification-algorithm-based-on-near-infrared-spectroscopy-and-random-forest.
BibTeX@misc{4ortxyz_an-efficient-tea-quality-classification-algorithm-based-on-near-infrared-spectroscopy-and-random-forest_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An efficient tea quality classification algorithm based on near infrared spectroscopy and random Forest}}, year = {2026}, url = {https://4ort.xyz/entity/an-efficient-tea-quality-classification-algorithm-based-on-near-infrared-spectroscopy-and-random-forest}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): An efficient tea quality classification algorithm based on near infrared spectroscopy and random Forest — https://4ort.xyz/entity/an-efficient-tea-quality-classification-algorithm-based-on-near-infrared-spectroscopy-and-random-forest (retrieved 2026-05-24)
