Research on supply and demand matching model of transportation modes in MaaS system of integrated passenger transport hub based on deep learning

Abstract

Advances in artificial intelligence and data acquisition technology are growing, the research on deep learning algorithm has gone deep into various fields. At this stage, the demand supply matching model under the comprehensive passenger transport hub travel system is obtained by analyzing the travel mode data. This paper takes traffic time as the research direction,uses machine learning and complex network theory to conduct in-depth learning algorithm research, respectively discusses, explores and forecasts the traffic supply and demand mode data, and explores the traffic mode supply and demand model under the comprehensive passenger transport hub travel service system. It is shown in traffic data that using the prediction form of deep learning to predict traffic conditions and travel pressure can enable traffic managers to master traffic dynamics and lead the direction for future traffic development. Finally, from the perspective of MaaS system, the paper uses big data and information processing methods to explore the supply and demand matching model in terms of transportation modes. The research shows that MaaS system can make overall planning in terms of traffic resources, provide reasonable travel modes for traffic travelers and match corresponding travel services. It not only makes overall planning and guarantee for travel services, but also promotes the sustainable development of the transportation supply and demand system.

The synergistic evolution of supply-demand composite system for airport green development: A case study in Guangzhou Baiyun International Airport, China

“…Synergistic evolutionary analysis in composite systems exploration can investigate the interactive relationships and coordinated developmental processes among subsystems [ 21 ]. The concept of coevolution emerged in the 1970s with Herman Haken’s notion of synergetics, highlighting complex systems’ ability to internally coordinate and cooperate through self-organization, leading to systematic and ordered development [ 9 ]. In this process, the Haken model can identify the dominant co-evolutionary parameters of the composite system using the approximate adiabatic assumption mechanism [ 22 ].…”

“…Green airport development of is fundamentally a process in which this elements achieve coordinated development through interaction. In this process, research on the supply and demand sides is constrained by the development levels of each side, posing challenges in analyzing the supply-demand evolution relationship of airports in the process of green development from the comprehensive standpoint of the supply-demand composite system [ 9 ]. To establish a green and low-carbon airport development system and promote the comprehensive green transformation of civil aviation development, green development should be integrated into the airport supply-demand composite system.…”