Prediction of Air Pollution Interval Based on Data Preprocessing and Multi-Objective Dragonfly Optimization Algorithm

With the rapid development of global industrialization and urbanization, as well continuous expansion population, large amounts industrial exhaust gases automobile are released. To better sound an early warning air pollution, researchers have proposed many pollution prediction methods. However, traditional point methods cannot effectively analyze volatility uncertainty pollution. fill this gap, we propose a combined system based on fuzzy granulation, multi-objective dragonfly optimization algorithm probability interval, which can Experimental results show that not only predict changing trend data local characteristics but also provide strong technical support for