基于并行网元的短期集合日照预报方法

IF 0.4 4区 工程技术 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC
Shoji Kawasaki, Koshi Ishibe
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引用次数: 0

摘要

在本文中,作者提出了一种基于神经进化(NE)的多个体短时间前(1 h前)日照预测的集成预测方法,该方法将遗传算法应用于神经网络的学习算法。虽然该方法相对于单一预测提高了准确率,但NE存在训练时间长的问题。为了解决这一问题,作者提出了一种GPU处理短时预报的并行化方法,并尝试通过GPU的并行化来解决这一问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Short-Term Ensemble Insolation Forecasting Method Using Parallelized NE

In this paper, the authors propose an ensemble forecasting method using multiple individuals for short-time-ahead (1 h ahead) insolation forecasting by using neuroevolution (NE), in which a genetic algorithm is applied to the learning algorithm of a neural network for insolation. Although the method improves the accuracy compared to a single forecast, NE has a problem that the training time is long. In order to solve this problem, the authors propose a parallelization method of GPU processing for short-time-ahead forecasting and try to solve the problem by parallelizing the GPU.

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来源期刊
Electrical Engineering in Japan
Electrical Engineering in Japan 工程技术-工程:电子与电气
CiteScore
0.80
自引率
0.00%
发文量
51
审稿时长
4-8 weeks
期刊介绍: Electrical Engineering in Japan (EEJ) is an official journal of the Institute of Electrical Engineers of Japan (IEEJ). This authoritative journal is a translation of the Transactions of the Institute of Electrical Engineers of Japan. It publishes 16 issues a year on original research findings in Electrical Engineering with special focus on the science, technology and applications of electric power, such as power generation, transmission and conversion, electric railways (including magnetic levitation devices), motors, switching, power economics.
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