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Prediction the Rice’s Yield per acre using Backpropagation Algorithm
http://hdl.handle.net/20.500.12678/0000003348
http://hdl.handle.net/20.500.12678/0000003348766d5c6d-1705-415e-aae8-52eae3357d52
b079cfe0-7fa0-4523-be54-b576435a6502
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psc2010paper (173).pdf (286 Kb)
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Article | ||||||
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Publication | ||||||
Title | ||||||
Title | Prediction the Rice’s Yield per acre using Backpropagation Algorithm | |||||
Language | en | |||||
Publication date | 2010-12-16 | |||||
Authors | ||||||
Phyu, Poe Ei | ||||||
Description | ||||||
Nowadays, Neural Network technologies areapplied in many fields. Neural Networks (NN) rely onthe inner structure of available data sets rather thanon comprehension of the modeled processes betweeninputs and outputs. Therefore, neural networks havebeen regarded as highly empirical models withlimited extrapolation capability to situations outsidethe range of the training and validation data sets.This paper introduces the predict yield in describefield with neural network using backpropagationalgorithm. This system is intended to compare theyield using training weights on all fields and the yieldusing training weights on each field. | ||||||
Keywords | ||||||
neural network, backpropagation algorithm | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/1108 | |||||
Journal articles | ||||||
Fifth Local Conference on Parallel and Soft Computing | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |