The Prediction Method Research Of Wheat Production Based On Least Square Support Vector Machines

Researching on the laws of grain production and carrying out scientific prediction ongrain yield are the fundamentals for making agricultural policies. This paper takes theproduction situation of wheat in Ningxia area as the research object and aims to establish aprediction modeling line with relevant knowledge of statistical learning theory and principlesof structural risk minimization by choosing proper scientific principles and predictionmethods, and will systematically processing and analyzing the model to research and realizethe wheat yield prediction system for grain production.This paper focuses on discussing the algorithm of Least Square Support Vector Machines(LS-SVM), determining the main factors affecting wheat yield in line with the growthfeatures of wheat by means of LS-SVM algorithm, a wheat yield prediction model has beenbuilt for the wheat yield in Ningxia area from1981to2010. The prediction results show thatthis model has high prediction accuracy. Meanwhile, the paper also researches suchtechnologies as preprocessing and graphical interface interaction etc. and has realized thewheat yield prediction system in Ningxia area. With good expansibility, this system can beused by relevant departments such as agricultural department, etc., and it will provide a newapproach for predicting grain yield.Firstly, this paper analyze and make study on the theoretical and application mechanismsof support vector machineand LS-SVM based on relevant contents of statistical learningtheory, and builds a prediction model of grain yield. Secondly, it has researched and improvedthe prediction algorithm on the basis of the wheat yield data in Ningxia area; it also carriesout relevant prediction and experimental analysis, and obtains the results of time seriesprediction of wheat yield based on LS-SVM. Analysis has showed that its prediction resultsare good. Then in view of the complicated growth process of wheat and the incompleteinformation, climate data is introduced as the main influencing factor affecting wheat yield toresearch and improve the corresponding data pre-processing technology. The paper proposes the method for wheat yield prediction based on LS-SVM and climate data. The experimentresults show that this method is superior to traditional time series prediction method. Inaddition, considering the multi-factor property of wheat production system, it also proposes aprediction method of LS-SVM based on time weight, aiming at increasing the predictionaccuracy. Finally, on the basis of the wheat yield prediction model based on LS-SVM andclimate data, the paper researches corresponding graphical interface interaction technologiesto conduct systematically development, thus forming the wheat yield prediction system inNingxia area.These experiments prove that the LS-SVM have not only covered some shortages ofsupport vector machine, but also have effectively increased the speed of large sample learningat the premise of ensuring the prediction accuracy.