Distributed HS-ARTMAP and its forecasting model for electricity load

doi:10.1016/j.asoc.2015.03.037

2015-07-01

PRE

DOI：10.1016/j.asoc.2015.03.037

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摘要

En 中文

Intelligence technology develops quickly to predict and respond to the actions of electric power users to maintain a reliable and secure electricity infrastructure. This paper proposed a new on-line training network called distributed hyper-spherical ARTMAP (dHS-ARTMAP) to forecast the electricity load. The new model constructs a more compact network structure and largely decreases the proliferation problem that Fuzzy ARTMAP models usually encounter. Experiments of short-term electricity load forecasting are made with the data from Queensland, Australia. Results are compared with other methods. The effectiveness of the dHS-ARTMAP network proves itself a promising alternative to put into practical use. (C) 2015 Elsevier B.V. All rights reserved.

Keyword:

Distributed hyper-spherical ARTMAP

(dHS-ARTMAP) model

Electricity load

Forecast

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期刊

Applied Soft Computing

IF:

6.6

论文数:

1.4W

被引数:

4.8W

机构

fudan university

学者数:

11.8W

论文数: 7.7W

被引数: 121

lanzhou university

学者数:

4.2W

论文数: 2.6W

被引数: 27

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