Research On The Model Of The Relationship Between The Environmental Factors And The Laying Performance Of Layer House Based On Improved BP Neural Network

This paper studies the relationship between the environmental factors and the laying performance of layer house in winter.Taking the automatic egg layer farm of Jinan Poultry Company,Susong County,Anqing City as the research object,the company's Hailan brown layer house was tested and analyzed for relevant environmental indicators and egg production index of the laying hens.The temperature,humidity,carbon dioxide,wind speed,light,ammonia concentration,and egg production of the layer house were determined in the layer house in different spatial locations in winter.In order to analyze the effect of multiple environmental factors on laying performance of layers in an airtight layer house,a model of the relationship between the environment factors and the performance of egg-laying in layer house based on CS and BP is presented.The basic model of neural network is constructed based on the parameters of main environmental factors(temperature,humidity,carbon dioxide,wind speed,illumination,ammonia)as input,and the egg production of hens as output.Aiming at the defect that BP neural network is easy to fall into local minimum,the algorithm is improved.Using a modified cuckoo search algorithm combined with BP neural network to establish a regression model for the relationship between microclimate environmental factors and laying performance in layer house.We tested the algorithm performance through concrete experiments.The experimental results show that: 1.The improved cuckoo algorithm has faster convergence speed and higher precision than traditional cuckoo algorithm;2.Compared with genetic algorithm,BP neural network optimization and particle swarm optimization BP neural network algorithm are compared.In the model,the improved cuckoo optimization BP neural network proposed in this paper improves the accuracy of fitting,and can more accurately reflect the relationship between environmental factors and laying performance.3.Compared with support vector machines,the improved BP neural network proposed in this paper The combined effect is significantly better.In this paper,based on the model of relationship between laying environment and laying performance based on the improved BP neural network,the relationship curve between environmental factors(temperature,humidity,carbon dioxide,wind speed,light,ammonia)and egg production is drawn.Further calculations of the optimal ideal environmental parameters for the house are: temperature 20°C,humidity %70,illumination 28 lx,carbon dioxide concentration 2000mg/m3,ventilation 0.52m/s,and ammonia concentration 0mg/m3.