北京交通大学学报2024，Vol.48Issue(5)：21-29,9.DOI:10.11860/j.issn.1673-0291.20230141
基于CNN-LSTM混合模型的航空公司机票价格预测
Airline ticket price prediction based on CNN-LSTM hybrid model
摘要
Abstract
To address the need for forecasting future trends in airline ticket prices in highly competitive markets,this paper proposes a CNN-LSTM hybrid model that integrates Convolutional Neural Net-work(CNN)and Long Short-Term Memory(LSTM).In the data construction and input phase,a channel data structure is developed to represent ticket prices,emphasizing the competitive relation-ships among airlines.Furthermore,various factors influencing ticket price fluctuations are considered,leading to the creation of independent channel data structures to represent airline attributes,flight attri-butes,and date attributes.These channel data are then integrated into a multi-channel data input for-mat suitable for CNNs.In the modeling phase,a one-dimensional Convolutional Neural Network(1D-CNN)is utilized to extract features from the multi-channel input data,while the LSTM captures tem-poral dependencies within the data to predict future ticket prices for different flights on a given route.The proposed CNN-LSTM model is compared against several baseline models,and ablation experi-ments are conducted to validate the importance of the selected influencing factors.Experimental results demonstrate that the CNN-LSTM model achieves significant improvements in prediction perfor-mance.Compared with Random Forest,Support Vector Machine,standalone CNN,standalone LSTM,and Vector Autoregression model,the Mean Absolute Error is reduced by 18.74%to 57.02%,and the Mean Absolute Percentage Error is reduced by 9.31%to 22.16%.Furthermore,the ablation experiments confirm that incorporating these influencing factors enhances the model's overall performance.The findings of this study not only provide decision-making support for airlines in ticket pricing and adjustment strategies but also introduce novel methodologies and perspectives for research in airline ticket price prediction.关键词
深度学习/机票价格预测/时间序列/卷积神经网络/长短期记忆网络Key words
deep learning/airline ticket prediction/time series/convolutional neural network/long short-term memory network分类
信息技术与安全科学引用本文复制引用
王夷龙,张生润,唐小卫,张崇横..基于CNN-LSTM混合模型的航空公司机票价格预测[J].北京交通大学学报,2024,48(5):21-29,9.基金项目
国家自然科学基金(U2233208) （U2233208）
民航安全能力建设项目(58I230071A23) （58I230071A23）
南京航空航天大学科研与实践创新计划(xcxjh20230741,xcxjh20220724) National Natural Science Foundation of China(U2233208) （xcxjh20230741,xcxjh20220724）
Civil Aviation Safety Building Project(58I230071A23) （58I230071A23）
Post-graduate Research&Practice Innovation Program of NUAA(xcxjh20230741,xcxjh20220724) （xcxjh20230741,xcxjh20220724）
