科技创新与应用2025，Vol.15Issue(16)：11-16,6.DOI:10.19981/j.CN23-1581/G3.2025.16.003
基于DBO-BP的飞机飞行碳排放量预测研究
余嵩涛 1钱宇 1董锐2
作者信息
- 1. 中国民用航空飞行学院 飞行技术学院,四川 广汉 618307
- 2. 中国民用航空飞行学院绵阳分院,四川 绵阳 621000
- 折叠
摘要
Abstract
To address the growing carbon emissions in the civil aviation sector and to enhance the monitoring and prediction of passenger aircraft carbon emissions,we have explored the development of a BP neural network model designed to forecast flight-related carbon emissions.The study employs the Dung Beetle Optimizer(DBO)to refine the weights and thresholds of the BP neural network.By performing Pearson correlation analysis on QAR data from an Airbus A320 aircraft,parameters with high correlation coefficients to carbon emissions were selected and input into the model.An evaluation and comparison of the accuracy and predictive performance of both models were performed.The results demonstrate that the DBO-BP neural network achieves an average prediction accuracy of 98.1%,while the average prediction accuracy of the standard BP neural network is 95.7%.The DBO-BP neural network achieved a 2.1%improvement in average prediction accuracy compared to the standard BP neural network.This study shows that optimizing the BP neural network with the dung beetle algorithm leads to enhanced prediction accuracy,thus providing algorithmic support for studies on low-carbon flight strategies and achieving green and low-carbon development in the civil aviation industry.关键词
DBO-BP/碳排量/蜣螂算法/神经网络/低碳飞行Key words
DBO-BP/carbon emissions/Dung Beetle Optimizer(DBO)/neural network/low-carbon flight引用本文复制引用
余嵩涛,钱宇,董锐..基于DBO-BP的飞机飞行碳排放量预测研究[J].科技创新与应用,2025,15(16):11-16,6.
