Planning model of a low-carbon landscape garden environment based on PSO-BP

Lin Han, Peng Li and Yuting Ruan

International Journal of Low-Carbon Technologies, 2025, vol. 20, 137-56

Abstract: A particle swarm optimization-back propagation neural network (PSO-BP) is proposed. First, we collect and preprocess the planning data for low-carbon landscape environment to ensure accuracy and consistency of data; then we propose the PSO-BP model that combines the global optimization characteristics of particle swarm algorithm and the nonlinear mapping capability of the backpropagation neural network. Empirical studies show that this model can effectively reduce energy consumption and carbon emissions, thus improving the ecological environment quality, improve the ecological service function, and effectively promote the sustainable development of low-carbon landscape buildings.

Keywords: PSO-BP; low-carbon; garden planning; natural environment；optimum design (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:oup:ijlctc:v:20:y:2025:i::p:137-56.

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