Green Development Path of Artificial Intelligence in China's Aviation Logistics

Abstract

This thesis aims to explore the paths through which artificial intelligence (AI) promotes the green development of China's aviation logistics industry. With the increasing global awareness of environmental protection and the Chinese government's emphasis on green development, aviation logistics, as one of the major fields of energy consumption and carbon emissions, faces the pressure of transformation and upgrading. By introducing advanced AI technologies such as machine learning, big data analysis, and intelligent scheduling systems, it is possible to optimize operational efficiency, reduce energy consumption, and minimize environmental pollution.

This thesis first reviews the domestic literature on the application of AI in the logistics industry, summarizes the main achievements and shortcomings of existing research. Secondly, it analyzes in detail the current development status of China's aviation logistics industry and the environmental challenges it faces. Then, it proposes various possible AI application scenarios and evaluates the actual effects of these scenarios through case studies or simulation experiments. Finally, based on the comprehensive results of the previous research, a series of strategic suggestions for promoting green development are provided for relevant government departments and enterprises, including policy support, technological innovation, and management model innovation