NDLI: Hybrid and constructive neural networks applied to a prediction problem in agriculture

Content Provider	IEEE Xplore Digital Library
Author	de Castro, L.N. von Zuben, F.J. Martins, W.
Copyright Year	1998
Description	Author affiliation: Dept. of Comput. Eng. & Ind. Autom., UNICAMP, Sao Paulo, Brazil (de Castro, L.N.)
Abstract	The application of artificial neural networks to the solution of problems in agriculture is rarely seen. Motivated by their great potential for dealing with nonlinear prediction tasks, two neural network architectures are independently used to implement alternative tools with the goal of predicting soya production: a hybrid architecture, based on a composition of a Kohonen self-organizing map and a multilayer perceptron, and a constructive architecture, based on projection pursuit learning. Whenever a low harvest is anticipated by the prediction tool, from a set of data extracted at the beginning of the life cycle of the plant, the ultimate purpose is to employ techniques for the correction of the soil composition, aiming at reversing the scene. The output to be predicted is a nonlinear function of a high number of input variables, which prevents the adoption of conventional prediction strategies. The two prediction tools presented here can be directly applied to all prediction problems of similar complexity in other research areas.
Starting Page	1932
Ending Page	1936
File Size	476737
Page Count	5
File Format	PDF
ISBN	0780348591
ISSN	10987576
DOI	10.1109/IJCNN.1998.687154
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1998-05-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Artificial neural networks Agriculture Multi-layer neural network Production Multilayer perceptrons Data mining Soil Layout Input variables
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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