A Fuzzy Neural Network Approach for Evaluation of Wetland Restoration Programmes

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 res...

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Bibliographic Details
Main Author: Linzi Li
Format: Article
Language:English
Published: Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek 2024-01-01
Series:Tehnički Vjesnik
Subjects:
Online Access:https://hrcak.srce.hr/file/457146
Description
Summary: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.
ISSN:1330-3651
1848-6339