Sugarcane growth prediction based on meteorological parameters using extreme learning machine and artificial neural network

Sugarcane growth prediction based on meteorological parameters using extreme learning machine and artificial neural network

Management strategies for sustainable sugarcane production need to deal with the increasing complexity and variability of the whole sugar system. Moreover, they need to accommodate the multiple goals of different industry sectors and the wider community. Traditional disciplinary approaches are unabl...

Full description

Bibliographic Details
Main Authors: Pezhman Taherei Ghazvinei, Hossein Hassanpour Darvishi, Amir Mosavi, Khamaruzaman bin Wan Yusof, Meysam Alizamir, Shahaboddin Shamshirband, Kwok-wing Chau
Format: Article
Language:English
Published: Taylor & Francis Group 2018-01-01
Series:Engineering Applications of Computational Fluid Mechanics
Subjects:
Sustainable production
sugarcane
machine learning: growth model
estimation
extreme learning machine
prediction
Online Access:http://dx.doi.org/10.1080/19942060.2018.1526119

Internet

http://dx.doi.org/10.1080/19942060.2018.1526119

Similar Items