%0 Journal Article
%T 基于PSO-BiLSTM的乐山市空气质量指数预测<br>Air Quality Index Forecast of Leshan City Based on PSO-BiLSTM
%A 陶诗仪
%A 余言
%A 张佳怡
%A 龚书琪
%A 董芸吟
%A 王靖涵
%A 高仕龙
%J Statistics and Applications
%P 130-140
%@ 2325-226X
%D 2025
%I Hans Publishing
%R 10.12677/sa.2025.145132
%X 随着工业化和城市化的快速发展&#65292;空气质量问题已成为全球关注的焦点。乐山市作为四川省的一个重要城市&#65292;也面临着空气质量下降的严峻挑战。为了有效预测和应对空气污染问题&#65292;本研究采用时间序列分析方法&#65292;使用双向长短期记忆网络、贝叶斯优化算法以及粒子群优化算法对乐山市的历史空气质量指数进行了深入分析与预测。<br>With the rapid development of industrialization and urbanization, air quality has become the focus of global attention. Leshan City, as an important city in Sichuan Province, is also facing the severe challenge of declining air quality. In order to effectively predict and deal with air pollution, this study adopts the method of time series analysis, and uses the bidirectional long short-term memory network, Bayesian optimization algorithm and particle swarm optimization algorithm to analyze and predict the historical air quality index of Leshan City.
%K 时间序列&#65292
%K 长短期记忆网络&#65292
%K 双向长短期记忆网络&#65292
%K 贝叶斯优化算法&#65292
%K 粒子群优化算法<br>Time Series
%K Long Short-Term Memory Network
%K Bidirectional Long Short-Term Memory Network
%K Bayesian Optimization Algorithm
%K Particle Swarm Optimization Algorithm
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=115322