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A Hybrid Fuzzy Wavelet Neural Network Model with Self-Adapted Fuzzy c-Means Clustering and Genetic Algorithm for Water Quality Prediction in Rivers
Joint Authors
Huang, Mingzhi
Yi, XiaoHui
Cai, Jiannan
Ying, Guangguo
Tian, Di
Liu, Hongbin
Zhang, Chao
Ruan, Jujun
Zhang, Tao
Kong, Shaofei
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-12
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Water quality prediction is the basis of water environmental planning, evaluation, and management.
In this work, a novel intelligent prediction model based on the fuzzy wavelet neural network (FWNN) including the neural network (NN), the fuzzy logic (FL), the wavelet transform (WT), and the genetic algorithm (GA) was proposed to simulate the nonlinearity of water quality parameters and water quality predictions.
A self-adapted fuzzy c-means clustering was used to determine the number of fuzzy rules.
A hybrid learning algorithm based on a genetic algorithm and gradient descent algorithm was employed to optimize the network parameters.
Comparisons were made between the proposed FWNN model and the fuzzy neural network (FNN), the wavelet neural network (WNN), and the neural network (ANN).
The results indicate that the FWNN made effective use of the self-adaptability of NN, the uncertainty capacity of FL, and the partial analysis ability of WT, so it could handle the fluctuation and the nonseasonal time series data of water quality, while exhibiting higher estimation accuracy and better robustness and achieving better performances for predicting water quality with high determination coefficients R2 over 0.90.
The FWNN is feasible and reliable for simulating and predicting water quality in river.
American Psychological Association (APA)
Huang, Mingzhi& Tian, Di& Liu, Hongbin& Zhang, Chao& Yi, XiaoHui& Cai, Jiannan…[et al.]. 2018. A Hybrid Fuzzy Wavelet Neural Network Model with Self-Adapted Fuzzy c-Means Clustering and Genetic Algorithm for Water Quality Prediction in Rivers. Complexity،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1136066
Modern Language Association (MLA)
Huang, Mingzhi…[et al.]. A Hybrid Fuzzy Wavelet Neural Network Model with Self-Adapted Fuzzy c-Means Clustering and Genetic Algorithm for Water Quality Prediction in Rivers. Complexity No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1136066
American Medical Association (AMA)
Huang, Mingzhi& Tian, Di& Liu, Hongbin& Zhang, Chao& Yi, XiaoHui& Cai, Jiannan…[et al.]. A Hybrid Fuzzy Wavelet Neural Network Model with Self-Adapted Fuzzy c-Means Clustering and Genetic Algorithm for Water Quality Prediction in Rivers. Complexity. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1136066
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1136066