JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2014, Vol. 44 ›› Issue (4): 22-30.doi: 10.6040/j.issn.1672-3961.0.2014.003

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Forecasting of real estate market based on particle swarm optimized neural network

HUA Jingxin1,2, BO Yuming1, CHEN Zhimin1   

  1. 1. School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, China;  2. Shandong Urban Construction Vocational College, Jinan 250103, Shandong, China
  • Received:2014-01-06 Revised:2014-07-02 Published:2014-01-06

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Abstract: Particle swarm optimization (PSO) had the defects of low precision, and that were easily to be trapped in local optimization. To solve these problems, an neural network based on improved PSO was proposed for forecasting the real estate market. This algorithm introduced chaos sequence to update the weight and threshold, which could improve the quality of samples, reduce the local optimization and enhance the global searching ability. In addition, the avoid factor was set, which could make the particles be away from low likelihood area. Simulation results showed that this algorithm improved the accuracy of the weight and threshold.

Key words: threshold, particle swarm optimization, neural network, chaos, weight

CLC Number: 

  • TP273
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