Rural Landscape Planning and Design of Greenway Construction Path Based on Embedded Neural Network

As a link in rural landscapes, greenways have been given a new mission in their design and construction. The greenway design based on embedded neural networks not only emphasizes its natural value as an ecological corridor but also pays attention to its multifunctionality as a community activity center. By simulating and predicting the usage of greenways, dynamic evaluation and adjustment of their sustainability can be achieved. This study proposes to use intelligent greenways as a carrier, analyze market demand, tourist preferences, and local cultural resources through embedded neural networks, and innovate the design of characteristic tourism products. For example, dynamically adjusting tourism routes and activity projects based on seasonal changes, festival celebrations, and other factors to create immersive tourism experiences with local characteristics. Dynamically adjusting tourism routes adopts high-performance computing platforms and advanced data analysis technologies to ensure real-time and accurate data processing and analysis. Build customizable algorithm models that can be quickly adjusted and optimized based on changes in market demand and tourist preferences. At the same time, utilizing intelligent recommendation systems to provide personalized tourism planning for tourists enhances the attractiveness and competitiveness of rural tourism. In terms of rural environmental beautification and improvement, this study advocates using greenways as the main line, combined with the application of embedded neural networks in plant configuration, landscape design, and environmental art.