With the occurrence of many Vespa mandarinia sightings, Washington has established various channels to encourage people to report Vespa mandarinia. This paper uses the Time Series to predict the latitude and longitude, and verify the prediction through Neural Network and Linear Regression Fitting the accuracy of the result. The relative error of bringing the prediction data into the Neural Network training model is 8.73%. Using SVM model in this paper, unverified date training and analysis were carried out on the original data, and the analysis results showed that the accuracy was 89.95% and the recall rate was 93%, demonstrating the good matching degree of the model. Finally using a Decision Tree Classification Model calculate the total weight corresponding to each unverified data through PYTHON programming.

Junman Yu, Chenkang Wei, Yue Fang, Rui Kong. Confirming the Buzz about Hornets. Academic Journal of Computing & Information Science (2021), Vol. 4, Issue 3: 77-82. https://doi.org/10.25236/AJCIS.2021.040312.

[1] Washington state officials locate Asian giant hornet nest [J]. Farm Industry News, 2020.

[2] First Asian giant hornet trapped in Washington [J]. Southeast Farm Press, 2020.

[3] Xia Bing, Research on Evaluation Methods Based on Mathematical Models [M]. Peking University Press, Heilongjiang University Press, 2017: 69-80.

[4] Yang Haimin, Pan Zhisong, Bai Wei. A review of time series forecasting methods [J].Computer Science, 2019, 460128-35.