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Application of a hybrid of least square support vector machine and artificial bee colony for building load forecasting

机译:最小二乘支持向量机与人工蜂群的混合在建筑负荷预测中的应用。

摘要

Accurate load forecasting is an important element for proper planning and management of electricity production. Although load forecasting has been an important area of research, methods for accurate load forecasting is still scarce in the literature. This paper presents a study on a hybrid load forecasting method that combines the Least Square Support Vector Machine (LSSVM) and Artificial Bee Colony (ABC) methods for building load forecasting. The performance of the LSSVM-ABC hybrid method was compared to the LSSVM method in building load forecasting problems and the results has shown that the hybrid method is able to substantially improve the load forecasting ability of the LSSVM method.
机译:准确的负荷预测是正确计划和管理电力生产的重要因素。尽管负荷预测一直是重要的研究领域,但文献中仍缺乏准确的负荷预测方法。本文提出了一种结合最小二乘支持向量机(LSSVM)和人工蜂群(ABC)方法进行建筑物负荷预测的混合负荷预测方法的研究。将LSSVM-ABC混合方法与LSSVM方法在建筑物负荷预测问题中的性能进行了比较,结果表明,该混合方法能够显着提高LSSVM方法的负荷预测能力。

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