现代电力2012，Vol.29Issue(2)：32-36,5.
基于粗糙集神经网络和元胞自动机的空间负荷预测
The Spatial Load Forecasting Based on Rough Set Neural Network and Cellular Automata
张文彬 1赵强 1周萌 1刘萌1
作者信息
- 1. 华北电力大学控制与计算机工程学院,北京102206
- 折叠
摘要
Abstract
Based on the analysis of the current spatial load forecasting methods, an improved spatial load forecasting method is presented in this paper, in which rough set theory is used to simplify the sets of random data samples extracted from the spatial database, which can reduce the input variables and the number of samples for artificial neural network, and improve the convergence speed and accuracy of conversion rules of cellular automata extracted by the neural network. The method combines the advantages of the rough set and artificial neural network, and the cellular automata theory is used to simulate the urban land use types, then spatial load is forecasted. In the end, experiment of spatial load forecasting on one urban planning area verifies the effectiveness of this method.关键词
粗糙集/人工神经网络/元胞自动机/空间负荷预测/空间数据库Key words
rough set/ artificial neural network/ cellular automata/ spatial load forecasting/ spatial database分类
信息技术与安全科学引用本文复制引用
张文彬,赵强,周萌,刘萌..基于粗糙集神经网络和元胞自动机的空间负荷预测[J].现代电力,2012,29(2):32-36,5.
