The Application in Grain Monitoring Based on Particle Swarm-Fuzzy Neural Network Algorithm

In order to strengthen the administration of the barn, we need to storage environment for scientific and effective monitoring and analysis. This paper firstly filter and merge the temperature and humidity information in the environment by using fuzzy neural network, then regard the temperature and humidity as particles, calculate the fitness of the particles according to corresponding mildew rate and cost, finally the outputs of temperature and humidity curve values are obtained through iterative optimization of local and global extreme by particle swarm algorithm.