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January 2020 Mathematical prediction of the Jatropha curcas L. plant yield: comparing Multiple Linear Regression and Artificial Neural Network Multilayer Perceptron models
Afr. J. Appl. Stat. 7(1): 933-943 (January 2020). DOI: 10.16929/ajas/2020.933.248

Abstract

The aim of this study was to predict the Jatropha curcas plant yield through an Artificial Neural Network (ANN) Multi-Layer Perceptron (MLP) model. The predictive ability of the developed model was tested against the Multiple Linear Regression (MLR) using performance indexes. According to the performance indexes the use of ANN-MLP model improved Jatropha curcas plant yield prediction comparatively to MLR model.

L'objectif de cette étude est de prédire le rendement de la plante Jatropha curcas avec un modèle de réseau de neurones artificiels (ANN) perceptron multicouches (MLP). La capacité prédictive du modèle développé est testée par rapport à la régression linéaire multiple (MLR) en utilisant des indices de performance. Selon les indices de performance, l'utilisation du modèle ANN-MLP améliore la prédiction de rendement de Jatropha curcas comparativement au modèle MLR.

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"Mathematical prediction of the Jatropha curcas L. plant yield: comparing Multiple Linear Regression and Artificial Neural Network Multilayer Perceptron models." Afr. J. Appl. Stat. 7 (1) 933 - 943, January 2020. https://doi.org/10.16929/ajas/2020.933.248

Information

Published: January 2020
First available in Project Euclid: 1 February 2021

Digital Object Identifier: 10.16929/ajas/2020.933.248

Rights: Copyright © 2020 The Statistics and Probability African Society

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Vol.7 • No. 1 • January 2020
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