人工神经网络- Bat混合元启发式算法在苏尔坦阿兹兰沙水电站发电量和用水量预测中的应用

S. Hussin, M. Malek, N. S. Jaddi, Z. Hamid
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引用次数: 5

摘要

水力发电是可再生能源中具有大规模商业可行性的技术之一。将元启发式人工神经网络(ANN)技术与蝙蝠算法(BA)相结合,提出了一种预测霹雳河上游苏丹阿兹兰沙水电站未来发电量和用水量的仿生算法。在本研究中,设计并明确编写了人工神经网络和混合人工神经网络-蝙蝠算法编码,以定制本研究中使用的时间序列输入数据和假设。将人工神经网络与混合人工神经网络-人工神经网络的结果进行了比较。仿真结果表明,该混合算法明显优于传统的人工神经网络。
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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
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.
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