| 基于GRNN的输电线路覆冰厚度预测方法研究 |
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| 引用本文： | 蓝道林,郑振华.基于GRNN的输电线路覆冰厚度预测方法研究[J].电气技术,2010(12):27-30. |
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| 作者姓名： | 蓝道林 郑振华 |
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| 作者单位： | 1. 衢州电力局,衢州,浙江,324000
2. 太原理工大学,太原,030024 |
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| 摘 要： | 为了保障输电网的安全运行,输电线路覆冰厚度预测极为重要。本文还将人工神经网络原理引入输电线路覆冰厚度预测中,并针对BP网络收敛速度慢、已陷入局部极小的缺陷,提出了基于广义回归神经网络(GRNN)的预测模型。实例研究证明GRNN模型相比较BP模型,能更有效地预测输电线路覆冰厚度。
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| 关 键 词： | 输电线路覆冰厚度预测 人工智能 BP神经网络 GRNN神经网络 |
The Study on The Prediction Method of Ice Thickness of Transmission Line Based on The Combination of GRNN Neural Network |
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| Lan Daolin,Zheng Zhenhua.The Study on The Prediction Method of Ice Thickness of Transmission Line Based on The Combination of GRNN Neural Network[J].Electrical Engineering,2010(12):27-30. |
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| Authors: | Lan Daolin Zheng Zhenhua |
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| Affiliation: | Lan Daolin1 Zheng Zhenhua2(1.College of Electrical and Power Engineering Taiyuan University of Technology,Taiyuan 030024,2.Quzhou Electric Power Corporation,Quzhou,Zhejiang 324000) |
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| Abstract: | It is very important to forecast the ice thickness of Transmission Line for the safe operation of transmission network.The author had introduced artificial neural network(ANN) to the prediction of the ice thickness of transmission line,and proposed a predictive model based on GRNN addresses on the defects of BP network includes slow convergence and easiness of running to local minimum,and finally proved that GRNN model was more effective to predict the ice thickness of transmission line the BP model. |
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| Keywords: | prediction of the ice thickness artificial intelligence BP neural network GRNN neural network |
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