Optimization of digital landscape design system based on biomechanical simulation and machine learning algorithm in landscape architecture planning
Abstract
This paper presents a digital landscape design system that integrates biomechanical simulation and machine learning algorithms for improved vegetation growth prediction and environmental adaptability. Using finite element analysis (FEM) and the GreenLab model, the system simulates plant growth dynamics, while deep learning and genetic algorithms optimize landscape layouts. The system improves vegetation stability, wind resistance, and ecological efficiency, providing a more accurate and efficient approach to intelligent landscape planning.
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