Abstract

AbstractWith the rapid growth of urbanization and industrialization, the strain on resources and the environment has intensified, resulting in challenges such as soil erosion and biodiversity loss. To address these issues, the development of a circular economy and eco‐cities has become crucial. This article proposes an ecosystem assessment model based on the backpropagation neural network (BPNN) that incorporates environmental carrying capacity and energy regeneration capacity. The model aims to evaluate the ecological service value of wetlands in the Changjiang River basin. The results demonstrate that the proposed model outperforms other comparison methods, exhibiting a high level of accuracy. Furthermore, the simulation outcomes indicate that enhancing eco‐efficiency can enhance the environmental carrying capacity and energy regeneration capacity of the ecosystem, ultimately leading to an overall improvement in ecosystem value.

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