COMBINATION OF ARTIFICIAL NEURAL NETWORKS FOR PREDICTION OF COTTON NITROGEN STATUS FROM LEAF REFLECTANCE SPECTRA

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" COMBINATION OF ARTIFICIAL NEURAL NETWORKS FOR PREDICTION OF COTTON NITROGEN STATUS FROM LEAF REFLECTANCE SPECTRA "

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	151191
Doc. No	:	ET22983
Main Entry	:	Liangjiang Wang
Title Proper	:	COMBINATION OF ARTIFICIAL NEURAL NETWORKS FOR PREDICTION OF COTTON NITROGEN STATUS FROM LEAF REFLECTANCE SPECTRA
Note	:	This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract	:	This thesis work applies neural networks to the prediction of nitrogen INs statusof cotton plants from leaf reflectance spectra. Plant N status is an important parameterfor crop yield. Previous studies suggest leaf reflectance may be used to sense plant Nstatus (Penuelas and Filella 1998). In this work, neural networks are applied to twoclassification problems using reflectance spectra: one is to assess the possibility of N-deficiency during the later growth stage and the other is to predict cotton leaf Nconcentration.The diagnosis of N deficiency may be considered as a binary classificationproblem. Three different types of classifiers are constructed using the back-propagationalgorithm, radial basis functions (RBF), and learning-....,....-...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject	:	Electericl tess
	:	برق
electronic file name	:	TL46212.pdf
Title and statement of responsibility and	:	COMBINATION OF ARTIFICIAL NEURAL NETWORKS FOR PREDICTION OF COTTON NITROGEN STATUS FROM LEAF REFLECTANCE SPECTRA [Thesis]