Study On Prediction Model Of Strawberry Growth Based On Multi Element Collision

Strawberry origin in South America,China and Europe and other places.There are many Strawberry origin in South America,China and Europe and other places.There are many varieties of strawberries,in the world a total of more than 2,000 kinds,but a large area of cultivation of fine varieties are only dozens of species,of which strawberry cultivation methods mostly planted mainly.At present,China's demand for strawberries continues to improve,but the supply is very scarce,so it is necessary to establish a multi-factor collision impact shed greenhouse strawberry growth mathematical model.In this paper,the model of strawberry growth was established by using the theory of actual contact,and the growth of strawberry was predicted by using collision algorithm and improved BP neural network.Greenhouse technology for strawberry cultivation of the primary means,the development of greenhouses has a long history,but now China's greenhouse technology is still lagging behind the outstanding green technology abroad,the first foreign use of modern information technology and greenhouses combined technology,making shed strawberry production And quality are higher than our country.In this paper,we combine the information technology with the biotechnology to find the factors that affect the growth of strawberries,find the collision strength between these factors by collision algorithm,select the elements with high collision strength,and then build the sheds through the optimized BP neural network Strawberry growth model.This paper is mainly designed to three major modules.First of all,this paper has done some analysis on the problem of multi-factor collision,and analyzed the factors that affect the multi-factor factors of strawberry,and the relationship between the external characteristics of strawberry and the growth of strawberry is found by reading the related strawberry literature.Then through the computer field collision algorithm,the strawberry in the external characteristics of the collision relationship is selected more strongly.Secondly,three different models of multi-factor prediction are introduced respectively.The process of theoretical knowledge and related modeling is introduced for three different prediction models.By contrast,it can be found that BP neural network has a great advantage in predicting the growth model of multi-factors,so BP neural network is used as a model to predict strawberry.Finally,although the prediction accuracy of BP neural network model is high,but the standard BP neural network model itself still exists some of these defects,so this paper proposes an optimization method makes BP neural network algorithm in the prediction process of convergence speed and prediction accuracy are Has improved.The results show that BP neural network is superior to gray model and multiple linear regression in the establishment of strawberry growth model,but there are still many shortcomings in BP neural network.Therefore,this paper chooses multi-factor factor by collision algorithm The BP neural network is optimized by the optimization method,which makes the accuracy of the BP neural network in the prediction process and the convergence speed in the prediction process.This paper not only applies the theory to study the influence of multi-factor collision on the growth of strawberry,but also applies the forecasting model to intelligent agriculture greenhouse,and applies the forecasting model to practice.