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An extreme learning machine optimized by differential evolution and artificial bee colony for predicting the concentration of whole blood with Fourier Transform Raman spectroscopy
Research article (Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, 2023) · cited 16× · AI/ML
An extreme learning machine optimized by differential evolution and artificial bee colony for predicting the concentration of whole blood with Fourier Transform Raman spectroscopy is a scholarly article[1].
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An extreme learning machine optimized by differential evolution and artificial bee colony for predicting the concentration of whole blood with Fourier Transform Raman spectroscopy's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). An extreme learning machine optimized by differential evolution and artificial bee colony for predicting the concentration of whole blood with Fourier Transform Raman spectroscopy. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-extreme-learning-machine-optimized-by-differential-evolution-and-artificial-bee-colony-for-predicting-the-concentrati
MLA“An extreme learning machine optimized by differential evolution and artificial bee colony for predicting the concentration of whole blood with Fourier Transform Raman spectroscopy.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-extreme-learning-machine-optimized-by-differential-evolution-and-artificial-bee-colony-for-predicting-the-concentrati.
BibTeX@misc{4ortxyz_an-extreme-learning-machine-optimized-by-differential-evolution-and-artificial-bee-colony-for-predicting-the-concentrati_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An extreme learning machine optimized by differential evolution and artificial bee colony for predicting the concentration of whole blood with Fourier Transform Raman spectroscopy}}, year = {2026}, url = {https://4ort.xyz/entity/an-extreme-learning-machine-optimized-by-differential-evolution-and-artificial-bee-colony-for-predicting-the-concentrati}, note = {Accessed: 2026-05-24}}
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