Mathematical prediction of the Jatropha curcas L. plant yield: comparing Multiple Linear Regression and Artificial Neural Network Multilayer Perceptron models

C. Gbèmavo
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引用次数: 1

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 J.~curcas plant yield prediction comparatively to MLR model
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麻疯树产量的数学预测:多元线性回归与人工神经网络多层感知器模型的比较
利用人工神经网络(ANN)多层感知器(MLP)模型对麻疯树进行产量预测。利用性能指标对所建立模型的预测能力进行多元线性回归(MLR)检验。根据性能指标,采用人工神经网络- mlp模型对麻麻植株产量预测进行了较MLR模型的改进
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