Comparative analysis of hybrid models of firefly optimization algorithm with support vector machines and multilayer perceptron for predicting soil temperature at different depths

Comparative analysis of hybrid models of firefly optimization algorithm with support vector machines and multilayer perceptron for predicting soil temperature at different depths

This research aims to model soil temperature (ST) using machine learning models of multilayer perceptron (MLP) algorithm and support vector machine (SVM) in hybrid form with the Firefly optimization algorithm, i.e. MLP-FFA and SVM-FFA. In the current study, measured ST and meteorological parameters...

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Bibliographic Details
Main Authors: Shahaboddin Shamshirband, Fatemeh Esmaeilbeiki, Davoud Zarehaghi, Mohammadreza Neyshabouri, Saeed Samadianfard, Mohammad Ali Ghorbani, Amir Mosavi, Narjes Nabipour, Kwok-Wing Chau
Format: Article
Language:English
Published: Taylor & Francis Group 2020-01-01
Series:Engineering Applications of Computational Fluid Mechanics
Subjects:
firefly optimization algorithm
soil temperature
artificial neural networks
hybrid machine learning
prediction
Online Access:http://dx.doi.org/10.1080/19942060.2020.1788644

Internet

http://dx.doi.org/10.1080/19942060.2020.1788644

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