APPLICATION OF HYBRID PARTICLE SWARM ALGORITHM IN GRAIN STORAGE ENVIRONMENT

In order to ensure safety of grain storage environment,we need to strictly control the internal and external factors,such as humidity and temperature.We applied the PSO-BP neural network technology to a grain measurement and control system to achieve fusion processing of temperature and humidity data in different positions of the same granary so as to enhance the accuracy and stability of target parameter measurement.Firstly,the grain storage data were fused for the first time by the BP neural network;secondly,we applied PSO to process the fusion result.The method can achieve optimization of homogeneous data while generally considering the data complementary,thereby improving the reliability of the measurement and control system.