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Application of Swarm Intelligence Algorithms to Optimize the Power Consumption Model

机译:群智能算法在优化功耗模型中的应用

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This paper presents the problem of power consumption mathematical model development using the Pamir, the region of Tajikistan, as a case. The model view illustration describing the load curve is known, it is required to find the model parameters values. The paper compares three approaches: manual selection; deterministic method based on Fourier transform with local gradient search; meta-heuristic swarm algorithms. It is shown that swarm algorithms, due to their multipurposeness and scalability, make it possible to obtain more accurate models with less labor costs. But it is necessary to use several swarm algorithms, since it is impossible to determine in advance which one will be the best solution for a specific task. The results were confirmed by the application for the load curves of the UPS of Siberia.
机译:本文介绍了塔吉克斯坦地区使用PAMIR的功耗数学模型开发问题,如案例。描述了描述负载曲线的模型视图插图是已知的,需要找到模型参数值。本文比较了三种方法:手动选择;基于傅里叶变换的局部梯度搜索的确定方法; Meta-heuristic群算法。结果表明,由于它们的多态性和可扩展性,群算法使得可以获得更准确的模型,劳动力较少。但有必要使用几种群算法,因为不可能预先确定哪一个是特定任务的最佳解决方案。结果是通过施用Siberia的载荷曲线来证实结果。

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