Improving Inference of Biochemical Composition in Marine Biomass via Genetic Algorithm-Based Feature Selection on Raman Spectroscopic Data-Reference-Cited by-同舟云学术

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Improving Inference of Biochemical Composition in Marine Biomass via Genetic Algorithm-Based Feature Selection on Raman Spectroscopic Data

Published:2024-06-30 Issue: Volume:5 Page:01-08
ISSN:
Container-title:2024 IEEE Congress on Evolutionary Computation (CEC)
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Author:

Demir Kaan¹,Nguyen Bach H.¹,Rooney Jeremy S.²,Xue Bing¹,Zhang Mengjie¹,Lagutin Kirill³,MacKenzie Andrew³,Gordon Keith C.²,Killeen Daniel P.⁴

Affiliation:

1. Centre for Data Science and Artificial Intelligence & School of ECS, Victoria University of Wellington

2. University of Otago,Department of Chemistry,Dunedin,New Zealand

3. Callaghan Innovation,Lower Hutt,New Zealand

4. The New Zealand Institute for Plant and Food Research Limited,Nelson,New Zealand

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10609966/10611750/10612136.pdf?arnumber=10612136

Reference26 articles.

1. Managing Freshwater Fish in a Changing Climate: Resist, Accept, or Direct

2. An overview on significance of fish nutrition in aquaculture industry;Prabu;International Journal of Fisheries and Aquatic Studies,2017

3. Raman Spectra of Biological Samples: A Study of Preprocessing Methods

4. Genetic Algorithm for Feature and Latent Variable Selection for Nutrient Assessment in Horticultural Products

5. Vibrational Spectroscopy and Chemometrics for Rapid, Quantitative Analysis of Bitter Acids in Hops (Humulus lupulus)

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