A classification algorithm for door and window air tightness detection based on particle swarm optimization

Abstract

In the modern construction technology industry, on-site gas tightness detection is widely used in building doors and Windows, which can reduce unnecessary energy consumption in the application process of building, and achieve energy conservation and emission reduction targets. In order to increase the speed and efficiency of field detection of doors and Windows, this paper proposes a data transmission method based on WIFI wireless transmission, combines the particle swarm with CART algorithm to classify the detection data in real time, and uses this algorithm to optimize CART algorithm to improve the classification accuracy. We demonstrate the effectiveness through numerical simulation experiments.