Research on the spatio-temporal characteristics of hornets’ nests based on K-means clustering

Abstract

Asia giant hornet is a predator of European honeybees, invading and destroying their nests. Nowadays, the State of Washington is suffering the attack of this hornet. Due to the potential severe impact on local honeybee populations, it will probably cause a great deal of anxiety.The most informative factors we consider are Detection Date,latitude and longitude. We propose a “time-space-state model” to evaluate the information evaluated by these two indicators. The time-space-state model can be divided into two kinds: the general model of time discretization and space continuum; The general model of space discretization and time semi-continuity. In the previous model, we mainly use K-means algorithm to determine the nest position in discrete time. In the latter model, we use the improved K-means algorithm to obtain the distribution model of hornets with seasonal variation.Through research, we have discovered the temporal and spatial laws of hornets’ nests, which are of great significance for maintaining the stability of agricultural production.