基于ABC算法优化BP神经网络的雾霾天气预测模型研究

Study on Forecasting Model of Haze Weather Based on ABC Algorithm to Optimize BP Neural Network

本文首先阐述了BP神经网络和ABC算法的基本概念,结合现阶段环境空气质量需求,明确了雾霾天气预测预警的必要性,然后结合安徽省大气质量指数数据,从空气质量等级评估、预测指标体系构建和雾霾天气预测模型选择等方面,研究了基于ABC算法优化BP神经网络的雾霾天气预警模型,以期进一步提高雾霾等级评估与预测的准确性,提高政府相关部门决策的时效性。

This paper first expounded the basic concepts of BP neural network and ABC algorithm,combined with the current ambient air quality requirements,clarified the necessity of forecasting and early warning of smog weather.Then combining with Anhui Province's air quality index data,from the aspects of air quality rating assessment,con?struction of prediction index system and selection of haze weather forecasting model,a haze weather early warning model based on ABC algorithm to optimize BP neural network model was studied,with a view to further improving the accuracy of the assessment and prediction of the haze level and the timeliness of decision-making by relevant govern?ment departments.