Forecast of wind speed based on MLP network model using Levenberg Marquardt and gradient descent algorithms in Tetouan city, Northern Morocco

IF 1.5 Q4 ENERGY & FUELS Wind Engineering Pub Date : 2024-01-13 DOI:10.1177/0309524x231215812

Wissal Masmoudi, Abdelouahed Djebli

引用次数: 0

Abstract

This study aims to find the most powerful algorithm between LM and GD, applying them to the multilayer neural network (MLP) to predict the wind speed of the city of Tetouan. To achieve this we will use the meteorological data of this city from 31/07/2017 to 31/08/2022. The MLP adopted for our study is composed of two hidden layers, 30 neurons in the first layer and 15 in the second, 7 inputs and one output. The data is divided into 80% for training and 20% for testing. The results obtained showed that the Levenberg-Marquardt (LM) algorithm is more efficient than the gradient descent (GD) algorithm with a correlation coefficient R = 0.988102 and a mean square error MSE = 0. 0458. These results will allow us to accurately predict the wind speed of August for the year 2022 in this city.

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使用 Levenberg Marquardt 和梯度下降算法，基于 MLP 网络模型预测摩洛哥北部德图安市的风速

本研究旨在找出 LM 和 GD 之间最强大的算法，并将其应用于多层神经网络 (MLP)，以预测特图安市的风速。为此，我们将使用该市从 2017 年 7 月 31 日至 2022 年 8 月 31 日的气象数据。我们的研究采用的 MLP 由两个隐藏层组成，第一层有 30 个神经元，第二层有 15 个神经元，7 个输入和 1 个输出。数据分为 80% 用于训练，20% 用于测试。结果显示，Levenberg-Marquardt（LM）算法比梯度下降（GD）算法更有效，相关系数 R = 0.988102，均方误差 MSE = 0.0458。这些结果将使我们能够准确预测该城市 2022 年 8 月的风速。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Wind Engineering ENERGY & FUELS-

CiteScore

4.00

自引率

13.30%

发文量

期刊介绍： Having been in continuous publication since 1977, Wind Engineering is the oldest and most authoritative English language journal devoted entirely to the technology of wind energy. Under the direction of a distinguished editor and editorial board, Wind Engineering appears bimonthly with fully refereed contributions from active figures in the field, book notices, and summaries of the more interesting papers from other sources. Papers are published in Wind Engineering on: the aerodynamics of rotors and blades; machine subsystems and components; design; test programmes; power generation and transmission; measuring and recording techniques; installations and applications; and economic, environmental and legal aspects.