Urban Landscape Design Optimization System Based on Improved Particle Swarm Optimization Algorithm
摘要
We proposed an improved particle swarm optimization algorithm for urban landscape planning. The introduction of uncertainty dynamic inertia weight coefficients compensates for global search performance and local total lift of particle swarm optimization algorithms. As a result of simulation, it was found that this method has a significant advantage in terms of global convergence speed, convergence accuracy, and optimization performance.