基于PSO-BP神经网络的微波加热温度预测研究

Research on microwave heating based on BP neural network optimized by the particle swarm optimization algorithm

针对微波加热物料难以建立准确模型的问题,采用粒子群算法优化BP神经网络后,对微波加热物料的温度变化构建系统模型。在该模型上,对温度的变化趋势进行预测。实验结果表明,经过粒子群算法优化后的BP网络,具有更高的精度,预测能力显著提高。

For the microwave heating of materials is difficult to establish an accurate model, using particle swarm optimization algorithm to optimize BP neural network, aiming at temperature changes of microwave heating of materials, building the system model. On this model, the temperature trends are predicted. Experiment results show that, the BP network through particle swarm optimization algorithm optimized, with high accuracy and faster convergence, significantly improve the predictive ability.