Research On The Intelligent Distribution And Prediction For Crop Water

With the unbalanced between supply and demand of water resources,the development of water-saving agriculture is imperative.Except the use of micro-irrigation sprinkler irrigation,drip irrigation and other advanced water-saving irrigation technology,in order to imply precise irrigation,the application of advanced information technology is also important.Based on the actual water demand of crops and the Internet of things technology,and imply reasonable irrigation system to improve the precision of irrigation and the utilization rate of water is of great importance.The intelligent irrigation can change the blindness and randomness in the process of irrigation based on large amounts of data analysis,on the other hand,it can reduce the management cost and improve the economic benefit at the same time.On the condition of the Internet of things of agriculture,this paper made a few main aspects of the work based on crop water resources allocation and prediction:(1)In order to solve the problems in the traditional immune optimization algorithm,the local search operator is added into the original immune optimization algorithm to improve the traditional immune optimization algorithm.At the same time,in order to speed up the iteration,and to prevent the algorithm to miss the optimal antibody solution in the process of iteration,the initial population is divided into two sub population to conduct parallel search,which to a certain extent,accelerates the speed of population search in this paper.(2)Based on the actual situation of corn and wheat in different growth cycle,when the water supply is sufficient,this paper proves the advantages of the improved immune optimization algorithm compared with the original immune optimization algorithm.At the same time,under the condition of insufficient irrigation,the improved algorithm coordinates the water allocation of the two kinds of crops in different growth cycle,to maximum the crop yield.(3)As for the current situation of unreasonable allocation and waste of water resources in the process of farmland irrigation,the traditional forecasting method is picking out two important parameters of support vector machine based on traditional empirical data,however,this forecast may not accurate.In order to solve the problem,this paper using the data provided by Shanghai rural website,applying the improved immune optimization algorithm and the particle swarm optimization algorithm into the parameter optimization of support vector machines,finally,forms a new support vector machine model.(4)Based on the actual agricultural data,the new support vector machine model is applied in actual crop water prediction.Through the function between the various factors that affect crop,the model can predict the amount of water needed at any time.By comparing the two kinds of intelligent algorithm,the paper proves the important role in the parameter optimization of the improved immune optimization algorithm and the improved particle swarm algorithm,which can provide the theoretical guidance for water-saving irrigation.Finally,the paper summarizes the full content and looks forward to the work which we can do in the future.