Research on Wasp population based on Gray Prediction and Fuzzy Analytic hierarchy process

Abstract

The invasion of exotic species should be paid attention to because of its severe consequences, and governments have constructed monitoring and tracking system to collect people’s sightings of species. For example, Asian giant hornet, an exotic species for North American countries was first discovered in September, 2019. Interpretations based on received reports are of essential to master the current situation of species and to predict its spread. However, there is a considerable number of mistake reports, it is necessary to select the most likely positive reports out of mountains of reports to be detailly investigate first. In this paper, two main problems are focused: interpretation of historical reports and strategy of prioritization. First of all, this paper preprocesses the image data based on Gaussian filtering and convolution neural network to make it as balanced as possible. In addition, the image consists of a wide range of array data. Proper treatment can improve the efficiency of analysis. Then, construct the GPSM model (Gray Predicting Spread Model) based on gray prediction to measure the spread of the pest. From the historical positive sighting location provided in the dataset, the GPSM model is able to output the predicted next location following the previous principle. If the distance between predicted location and current outbreak area are significant, a spread can be concluded. Tests for the GPSM model shows the model has a very high level of precision