STDAPM: Spatial and Temporal Distribution Analysis and Prediction Model of Bee Species based on Grey Model

Yongjia Lei, Zhiying Cui, Yuer Yang, Xiangjie Wang

Abstract: The presence of many different species of bees in nature increases the diversity of ecosystems. However, when the original ecology of bees is destroyed, related bees will migrate. Nevertheless, large-scale migratory behavior may seriously affect local bee populations or affect local agriculture. Thus, some migrations result in the invasion of exotic species when these bees are often considered agricultural pests. As a result of the emergence of these pests, countries must decide how to prioritize their limited resources for follow-up investigations. In this paper, a model is established to predict the emergence of wild silkworms, which can provide strong support for pest management. To predict how pests spread over time, we build a Grey Model to predict the spread of bees from the spatial and temporal distribution. In addition, we set up a two-dimensional Grey Model using longitude and latitude as two variables to predict the next bee's geographic location. At the same time, when predicting the occurrence time of bees, we form a sequence of the annual 12-month reported times of previous years and still use the Grey Model for data processing and prediction.