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Liguo Zhang
Agricultural University of Hebei

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Research on Grain Yield Prediction Method Based on Improved PSO-BP Liguo Zhang; Jiangtao Liu; Lifu Zhi
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 10: October 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i10.pp7404-7411

Abstract

Aimed at the highly nonlinear and uncertainty of grain yield changes, a new method for grain yield prediction based on improved PSO-BP is proposed. By introducing mutation operation and adaptive adjust of inertia weight, the problem of easy to fall into local optimum, premature, low precision and low later iteration efficiency of PSO are solved. By using the improved PSO to optimize BP neural network’s parameters, the learning rate and optimization capability of conventional BP are effectively improved. The simulation results of grain production prediction show that the predict accuracy of the new method is significantly higher than that of conventional BP neural network method, and the method is effective and feasible.
Co-Authors Jiangtao Liu Lifu Zhi