A new family of genetic algorithms for wavelength interval selection in multivariate analytical spectroscopy

By Héctor C. Goicoechea, Alejandro C. Olivieri. 2003

62 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Biomedical Engineering, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/dd2444295bc30f9fe43bc62fa143841b6d5da60c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Santiago A. Bortolato
2. E. Arancibia
3. Natalia Sorol
4. Alejandro C. Olivieri
5. Nicolaas (Klaas) M. Faber

In Biomedical Engineering

1. Santiago A. Bortolato
2. E. Arancibia
3. Natalia Sorol
4. Alejandro C. Olivieri

In Industrial and Manufacturing Engineering

1. Santiago A. Bortolato
2. E. Arancibia
3. Natalia Sorol
4. Alejandro C. Olivieri

Citations in the corpus

• Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice: A test field for variable selection methods (2010, methodology): “The version employed in the present case is the so-called ranked regions genetic algorithm (RRGA) already described [27], except that the calibration set is randomly divided into two subsets only once in each”