To enhance the accuracy of PM2.5 concentration predictions amidst inherent randomness and complexity, this paper introduces a novel prediction method called the Integrated Black-winged Kite Algorithm with Backpropagation (IBKA-BP). This approach improves the traditional Backpropagation (BP) neural network by optimizing its weights and thresholds, effectively addressing common issues such as slow convergence and the tendency to get trapped in local optima. Comparative analyses of prediction errors demonstrate that the IBKA-BP model outperforms other advanced PM2.5 concentration prediction model...
