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Hybrid metaheuristic of artificial neural network — Bat algorithm in forecasting electricity production and water consumption at Sultan Azlan shah Hydropower plant

机译:人工神经网络 - 苏丹阿兹兰沙河水电站预测电力生产和耗水量的杂交成分术

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Hydropower is one of the technologies in renewable energy that is commercially viable on a large scale. A hybrid of metaheuristic Artificial Neural Network (ANN) technique with Bat Algorithm (BA), a bio-inspired algorithm is proposed to forecast future electricity production and water consumption at Sultan Azlan Shah Hydropower Dam located upstream of Perak river. In this study, both the ANN and Hybrid ANN-Bat Algorithm coding was designed and written explicitly to tailor the time series input data and assumptions used in this study. Comparison on results obtained from ANN and the proposed hybrid ANN - BA was conducted. Simulations conducted in this study exhibited that the proposed hybrid algorithm is much superior then the conventional ANN.
机译:水电是可再生能源的技术之一,这些技术在大规模上是商业上可行的。一种抗BAT算法(BA)的综合性人工神经网络(ANN)技术的混合动力,提出了一种生物启发算法,以预测位于霹雳州上游的苏丹阿兹兰莎水电坝的未来电力生产和耗水。在本研究中,明确地设计和书写了ANN和Hybrid Ann-Bat算法编写,以定制本研究中使用的时间序列输入数据和假设。对从ANN和所提出的杂交ANN - BA获得的结果进行比较。本研究中进行的模拟表明,所提出的混合算法与传统的ANN有多高。

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