Prediction of wheat moisture content at harvest time through ANN and SVR modeling techniques

Prediction of wheat moisture content at harvest time through ANN and SVR modeling techniques

The grain moisture content at harvest time is a key factor that limits harvesting windows. The present study aimed to develop a new methodology to predict wheat moisture content by using multi-layer perceptron (MLP) and support vector regression (SVR) techniques. Five input variables included the nu...

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Bibliographic Details
Main Authors: Shamsollah Abdollahpour, Armaghan Kosari-Moghaddam, Mohammad Bannayan
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2020-12-01
Series:Information Processing in Agriculture
Subjects:
Artificial neural network
Cereal
Harvest
Model
Support vector machine
Online Access:http://www.sciencedirect.com/science/article/pii/S2214317319301696

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http://www.sciencedirect.com/science/article/pii/S2214317319301696

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