Research on Intelligent Pest Prediction of Based on Improved Artificial Neural Network

摘要

In order to improve the efficiency and accuracy of crop pest prediction, an intelligent prediction model for insect pests of fruit trees is proposed by combining artificial neural network and genetic algorithm. In order to overcome the disadvantages of single BP network, the network structure is constructed with the historical data of insect pests, the global optimization characteristic of genetic algorithm is obtained, and the weights and thresholds of neural network are trained to overcome the main shortcomings of the single BP network, which is easy to fall into local minimum. The model output is quickly and accurately forced into the target sample. By analyzing the test results, it can be obtained that this prediction method can accurately describe the occurrence degree of insect pests. Compared with the traditional BP artificial neural network, the prediction method is more accurate than that of the traditional BP artificial neural network. The prediction accuracy and degree of prediction have been greatly improved, and the prediction accuracy is as high as 91.67%. Based on this, the intelligent model is used to predict the insect pests of fruit trees, and a new way of thinking is established in the field of prediction of fruit tree pests, which greatly promotes the rapid development of agriculture. It has good application value.