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首页> 外文期刊>Latin America Transactions, IEEE (Revista IEEE America Latina) >An Empirical Analysis of MLP Neural Networks Applied to Streamflow Forecasting
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An Empirical Analysis of MLP Neural Networks Applied to Streamflow Forecasting

机译:MLP神经网络在流量预测中的实证分析

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摘要

Nowadays, in Brazil there is a large energy potential that comes from hydro mineral sources, which most part of the electricity consumed comes from this source. According to this, it is important emphasize that the decision-making related with planning of the operation of the reservoirs of hydroelectric plants has been done based mainly on preview knowledge of the flow. Thereby, this work aims to conduct an exploratory study about the Artificial Neural Networks type MLP to estimate which is the best setting to perform the stream flow forecast. This study was applied to the Grande River basin, in addition, with the achieved results, it was possible to observe that the search of appropriate parameters shows significant gains in the execution of the forecasts and can to reduce the error level obtained.
机译:如今,在巴西,巨大的能源潜力来自水力矿产资源,其中大部分电力消耗都来自该资源。据此,重要的是强调,与水力发电厂水库运行计划有关的决策主要基于水流的预知来完成。因此,这项工作旨在进行关于MLP型人工神经网络的探索性研究,以估计这是进行流量预测的最佳设置。这项研究被应用于格兰德河流域,此外,通过取得的成果,可以观察到,对适当参数的搜索在执行预测中显示出显着的收益,并且可以减少获得的误差水平。

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