Multilogistic regression by evolutionary neural network as a classification tool to discriminate highly overlapping signals: Qualitative investigation of volatile organic compounds in polluted waters

Áreas de investigación:

• Methodology - Machine learning

Año:

2008

Tipo de publicación:

Artículo

Autores:

• Hervás-Martínez, César
• Silva, M.
• Gutiérrez, Pedro Antonio
• Serrano, A.

Journal:

Chemometrics and Intelligent Laboratory Systems

Volumen:

92

Número:

2

Páginas:

179-185

BibTex:

@article{HSGS2008, author = "C{\'e}sar Herv{\'a}s-Mart{\'i}nez and M. Silva and Pedro Antonio Guti{\'e}rrez and A. Serrano", awards = "JCR (2008): 1.940 (category STATISTICS {\&}amp; PROBABILITY, position 11/92 Q1)", comments = "JCR (2008): 1.940 (category STATISTICS {\&}amp; PROBABILITY, position 11/92 Q1)", crossref = " ", journal = "Chemometrics and Intelligent Laboratory Systems", month = " ", note = "JCR (2008): 1.940 (category STATISTICS {\&}amp; PROBABILITY, position 11/92 Q1)", number = "2", pages = "179--185", title = "{M}ultilogistic regression by evolutionary neural network as a classification tool to discriminate highly overlapping signals: {Q}ualitative investigation of volatile organic compounds in polluted waters", url = "http://dx.doi.org/10.1016/j.chemolab.2008.03.005", volume = "92", year = "2008", }

Nota:

JCR (2008): 1.940 (category STATISTICS & PROBABILITY, position 11/92 Q1)

Comentarios:

JCR (2008): 1.940 (category STATISTICS & PROBABILITY, position 11/92 Q1)