scholarly journals Modelling of the Slope Solute Loss Based on Fuzzy Neural Network Model

2022 ◽  
Vol 42 (2) ◽  
pp. 677-688
Author(s):  
Xiaona Zhang ◽  
Jie Feng ◽  
Zhen Hong ◽  
Xiaona Rui
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Fuzzy Neural Network ◽  
Fuzzy Neural

Application of T-S Fuzzy Neural Network in the Assessment of River Ecosystem Health

2013 ◽  
Vol 726-731 ◽  
pp. 958-962 ◽  
Author(s):  
Zhen Chun Hao ◽  
Xiao Li Liu ◽  
Qin Ju
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Fuzzy System ◽  
Ecosystem Health ◽  
Fuzzy Neural Network ◽  
Evaluation Model ◽  
Fuzzy Model ◽  
River Ecosystem ◽  
Fuzzy Neural

Healthy river ecosystem has been acknowledged as the object of river management, which is crucial for the sustainable development of cities. Simple and practical evaluation methods with great precision are necessary for the evaluation of river ecosystem health. Fuzzy system has been widely used in evaluation and decision making for its simple reasoning and the adoption of experts knowledge. However, much artificial intervention decreases the precision. Neural network has a strong ability of self-leaning while it is not good at expressing rule-based knowledge. The T-S fuzzy neural network model combines the advantages of fuzzy system and neural network. In this paper, the T-S fuzzy neural network model was used to establish a river ecosystem health evaluation model. Results show that the combination of T-S fuzzy model and neural network eliminates the influences of subjective factors and improve the final precisions efficiently.

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