Reducing NIR prediction errors with nonlinear methods and large populations of intact compound feedstuffs

Measurement Science and Technology

Volumn 19, Issue 8, 2008, Pages

  Fernandez Ahumada E ^a   Fearn, T ^b   Gomez A ^a   Vallesquino, P ^a   Guerrero, J E ^a   Perez Marin D ^a   Garrido Varo, A ^a  

^a UNIVERSITY OF CÓRDOBA   (Spain)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

Artificial neural networks; Ingredients; Large population; NIRS; Non milled feed analysis; Nonlinear; Support vector machines

Indexed keywords

DEEP NEURAL NETWORKS; FORECASTING; INFRARED DEVICES; MANUFACTURE; NEAR INFRARED SPECTROSCOPY; NEURAL NETWORKS; SUPPORT VECTOR MACHINES;

INGREDIENTS; LARGE POPULATION; NIRS; NON-MILLED FEED ANALYSIS; NONLINEAR;

LEAST SQUARES APPROXIMATIONS;

EID: 48849089088     PISSN: 09570233     EISSN: 13616501     Source Type: Journal    
DOI: 10.1088/0957-0233/19/8/085601     Document Type: Article

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