A Fuzzy Neural Network Approach for Evaluation of Wetland Restoration Programmes

LI Linzi
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Abstract

: Wetland restoration work is crucial for ecosystem development, and how to scientifically evaluate wetland restoration programmes is the key to improve the effectiveness of wetland restoration. In order to solve the problems of inadequate judgement and human influence in the evaluation of wetland restoration programmes, this paper proposes a wetland restoration programme evaluation model based on Fuzzy Neural Network method, which is based on fuzzy theory and combines the adaptive function and self-learning function of neural network to evaluate three wetland restoration programmes. The results show that programme B is better than programmes A and C and is suitable for long-term application in wetland restoration work in this area. It is concluded that the use of Fuzzy Neural Network model to evaluate the wetland restoration programmes is more accurate, more personalised, and has a better operation rate, which is an important means of evaluating the wetland restoration programmes and an important guideline to carry out the wetland work.
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评估湿地恢复计划的模糊神经网络方法
:湿地恢复工作对生态系统发展至关重要,如何科学评价湿地恢复方案是提高湿地恢复效果的关键。为解决湿地恢复方案评价中存在的判断不足和人为影响等问题,本文提出了基于模糊神经网络方法的湿地恢复方案评价模型,该模型以模糊理论为基础,结合神经网络的自适应功能和自学习功能,对三种湿地恢复方案进行评价。结果表明,方案 B 优于方案 A 和 C,适合在该地区湿地恢复工作中长期应用。由此得出结论,利用模糊神经网络模型评价湿地恢复方案,准确性更高,个性化更强,运行率更好,是评价湿地恢复方案的重要手段,也是开展湿地工作的重要指导思想。
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