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摘要

本文旨在将人工神经网络模型应用于苏丹Gezira州2006年1月至2018年5月期间的用电量数据,并通过使用准牛顿采样和在线学习训练递归神经网络来预测该时期(2018年6月至2020年12月)的未来值。这项研究依赖于国家控制中心的数据。应用人工神经网络后,用Thiel系数来验证模型的有效性,由于人工神经网络的强度和准确性,本文推荐将人工神经网络应用于各种时间序列数据。
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(Application of Artificial Neural Networks Model for Forecasting Consumption of Electricity in Gezira State, Sudan (2006-2018: تطبيقات الشبكات العصبية الاصطناعية للتنبؤ باستهلاك الكهرباء في ولاية الجزيرة، السودان (2006-2018)
This paper aimed applying models of artificial neural networks to electricity consumption data in the Gezira state, Sudan for the period (Jan 2006- May 2018), and predicting future values for the period (Jun 2018- Dec 2020) by train a recurrent neural network using Quasi-Newton Sampling and using online learning. The study relied on data from the national control center. After applying artificial neural networks, The Thiel coefficient is used to confirm the efficiency of the model, and the paper recommends the use of artificial neural networks to various time series data due to their strength and Accuracy.
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