General aviation trajectory prediction plays a crucial role in enhancing safety and operational efficiency at non-towered airports. However, current research faces multiple challenges including variable weather conditions, complex aircraft interactions, and flight pattern constraints specified by general aviation regulations. This paper proposes a deep learning method based on stochastic processes aimed at addressing uncertainty issues in general aviation trajectory prediction. First, we design a probabilistic encoder–decoder structure enabling the model to output trajectory distributions rather than single paths, with regularization terms based on Lyapunov stability theory to ensure predicted trajectories maintain stable convergence while satisfying flight patterns. Second, we develop a multi-layer attention mechanism that accounts for weather factors, enhancing the model’s responsiveness to environmental changes. Validation using the TrajAir dataset from Pittsburgh-Butler Regional Airport (KBTP) not only advances deep learning applications in general aviation but also provides new insights for solving trajectory prediction problems.

This article is motivated by the challenge of the increasing power of e-commerce compared to traditional commerce. An online retail platform can provide both agency selling and reselling schemes, while the supplier can adopt one scheme or both. For a case study of Gree, we formulate four cases based on the channel structures to investigate the adoption strategies of platform schemes and their impacts on a traditional distributor, Jinghai. Firstly, we discuss the impacts of the slotting fee, the revenue-sharing proportion earned by the supplier, and the market competition intensity on the profits and decisions of members. A more intense market and a higher revenue-sharing proportion for the supplier will lead to a lower price in the traditional distribution channel. Secondly, we study how a supplier should employ the platform schemes with a traditional distributor. Particularly, the extremely low extra market demand driven by the online platform and the sufficiently low market intensity may not lead to a motivation for suppliers to adopt the agency scheme. Finally, Gree’s introduction of an agency scheme does not always spell disaster for traditional distributors, and it may not be such a bad thing for Jinghai to agree to Gree adding the online reselling scheme.