학술논문

Evaluation Model of Rubber Planting Suitability Based on Cloud Theory, Rough Set and Fuzzy Neural Network
Document Type
Conference
Source
2009 WRI Global Congress on Intelligent Systems Intelligent Systems, 2009. GCIS '09. WRI Global Congress on. 1:456-459 May, 2009
Subject
Computing and Processing
Rubber
Clouds
Fuzzy neural networks
Mathematical model
Fuzzy systems
Educational institutions
Feature extraction
Neural networks
Linearity
Intelligent systems
cloud model
rough set
fuzzy neural network
spatial clustering analysis
rubber planting
suitability
Hainan Province
Language
ISSN
2155-6083
2155-6091
Abstract
The new rubber planting suitability evaluation model based on the cloud theory, rough set and fuzzy neural network has been put forward according to the lack of influencing factors samples on rubber growth. Qualitative description of the rubber planting rules can be converted into quantitative rubber planting influencing factors sample data by the forward cloud generator of the evaluation model. Moreover, rough set is used to reduce the sample data. Then, the membership of each evaluation element is obtained via the fuzzy neural network. Finally, the evaluation grade is calculated though evaluation element membership. The preliminary research indicates that the model, which combines spatial clustering analysis, can scientifically and fleetly divide the study area into the most suitable area, suitable area, the less suitable area and unsuitable area.