Open AccessJournal Article
Comparison between powell algorithm and BP algorithm in training neural network
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TL;DR: The neural network optimization algorithm is used in faults diagnosis of the steam generating set (rotating mechanical equipment), and the fast calculation in weights values and threshold values of neural network are gained.
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Abstract: BP algorithm is often used in faults diagnosis of mechanical equipment.But BP network is apt to converge at the local minimum point.And,if the selected original parameters and network structure are not suitable,the divergent phenomenon will turn up in the network.SO this article advances that the neural network optimization algorithm is used in faults diagnosis of the steam generating set (rotating mechanical equipment),and the fast calculation in weights values and threshold values of neural network are gained.The neural network optimization algorithm result is compared with BP network algorithm result.It is shown that this method is faster and has higher accuracy than BP algorithm,and the neural network is absolutedly,convergent.
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Citations
Forecasting annual electricity demand using BP neural network based on three sub-swarms PSO
Ruiyou Zhang,Dingwei Wang +1 more
- 02 Jul 2008
TL;DR: A forecasting model combing back propagation (BP) neural network and three sub-swarms particle swarm optimization (THSPSO) is proposed, and the case study of Liaoning Province of China indicates that the network can be trained quickly by the hybrid algorithm of THS PSO and BP, and that annual electricity demand can be forecasted by this network with high precision.
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ANN with the Error Contracting Gradually Algorithm and Its Application in Generator Fault Diagnosis
Shuting Wan
- 11 Oct 2007
TL;DR: A new BP with the error contracting gradually algorithm is put forward that can avoid the excessive learning and learning error oscillation and two fault diagnosis models based on the new BP algorithm are set up respectively.