With 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.

中文翻译：

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长江流域生态环境价值评估与生态文明

随着城镇化、工业化快速发展，资源环境压力加剧，水土流失、生物多样性丧失等挑战日益凸显。为了解决这些问题，发展循环经济和生态城市变得至关重要。本文提出了一种基于反向传播神经网络（BPNN）的综合环境承载能力和能量再生能力的生态系统评估模型。该模型旨在评估长江流域湿地的生态服务价值。结果表明，所提出的模型优于其他比较方法，表现出很高的准确性。此外，模拟结果表明，提高生态效率可以增强生态系统的环境承载能力和能量再生能力，最终导致生态系统价值的整体提升。