The Application of BP Neural Network Learning Algorithm Based on the Particle Swarm Optimization

Zhi Hong Sun; Jun Wang; Bao Ji Xu

doi:10.4028/www.scientific.net/AMR.706-708.2057

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 706-708The Application of BP Neural Network Learning...

The Application of BP Neural Network Learning Algorithm Based on the Particle Swarm Optimization

Abstract:

The development of real estate has been affected by various social factors, including economic factors. BP neural network can more accurately forecast the trend of real estate industry according to economic development indicators. But BP neural network is slow convergence in the training process, and easily falls into local optimum. The BP neural network learning algorithm based on the particle swarm optimization (PSO) optimizes the weights and thresholds of the network by PSO algorithm, then to train BP neural network. The experimental results show that the performance of this new algorithm is better than BP neural network, but also has good convergence.

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Periodical:

Advanced Materials Research (Volumes 706-708)

Pages:

2057-2062

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.706-708.2057

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Online since:

June 2013

Authors:

Zhi Hong Sun, Jun Wang, Bao Ji Xu

Keywords:

BP Neural Network (BPNN), Particle Swarm Optimization (PSO), Prediction Model, Real Estate

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