信息工程大学学报2024，Vol.25Issue(4)：411-416,491,7.DOI:10.3969/j.issn.1671-0673.2024.04.006
利用神经网络预测的空气质量态势可视分析方法
Visual Analysis of Air Quality Situation Using Neural Network Prediction
叶林 1陈晓慧 1刘海砚 1张然 1刘涛1
作者信息
摘要
Abstract
At present,it is a challenge to present and analyz air quality prediction results from spatio-temporal perspective.Therefore,combining deep learning and big data analysis techniques,an interac-tive visual analysis method is proposed for multidimensional representation of air quality change dy-namics based on neural network prediction.Firstly,a multilayer two dimensional convolutional neural networks and long short-term memory neural network model(2D-CNN+LSTM)is proposed for extract-ing air quality spatio-temporal features for Air Quality Index(AQI)prediction.Secondly,from the prac-tical requirements,a visualization view and interaction method is designed for multidimensional repre-sentation of air quality situation information.Finally,a visual analysis system is constructed to utilize the air pollution dataset for case studies and analysis.The experimental results show that it can realize the spatial and temporal multidimensional expression and analysis of air quality situation through the synergistic interaction of multiple views such as time-series visualization,spatial visualization and at-tribute association visualization.It provides new ideas and methods for air quality prevention and man-agement problems.关键词
空气质量预测/时空态势分析/空气质量/可视分析/神经网络Key words
air quality prediction/spatio-temporal situation analysis/air quality/visual analysis/neural network分类
信息技术与安全科学引用本文复制引用
叶林,陈晓慧,刘海砚,张然,刘涛..利用神经网络预测的空气质量态势可视分析方法[J].信息工程大学学报,2024,25(4):411-416,491,7.
