基于PSO-EO算法优化的BP神经网络研究

Research on Optimizing BP Neural Network Based on PSO-EO

PSO算法优化的BP神经网络解决了其收敛速度慢或不收敛等缺点,但PSO算法本身却存在早熟和局部收敛的问题。为此引入EO算法,用EO算法与PSO算法相结合对BP神经网络进行改进。通过实验表明:EO算法与PSO算法结合优化的BP算法具有良好的收敛性和较高的预测精度,其性能优于传统的BP算法及PSO优化的BP算法。

The BP neural network is improved by PSO algorithm had solved the disadvantages of BP neural networks algorithm itself, such as slow convergence, non-convergence. But the PSO algorithm has it sells problems, such as precocity and local convergence, so the EO algorithm is introduced, and the BP neural network is improved by the combination of EO algorithm and PSO algorithm. The practice result indicates that the BP neural network improved by PSO-EO has good convergence and higher forecast accuracy, better than the traditional BP algorithm and BP algorithm optimized by PSO algoritm.