loading...
The BP Neural Network Optimizing Design Model for Agricultural Information Measurement Based on Multistage Dynamic Fuzzy Evaluation
Adelaide, Australia January 23-January 24
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/WKDD.2008.29First International Workshop on Knowl ...
 This Article 
 
PDF
HTML
 
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
The agricultural information level is on the initial stage in China, so we should pay more attention to its construction, but how to measure the agricultural information degree is a major issue. This paper overcomes the shortcoming of traditional linear agricultural information degree evaluation method, proposes a BP neural network evaluating method based on the multistage dynamic fuzzy judgment, takes the multistage dynamic fuzzy judgment as the sampling foundation, uses the BP neural network principle to establish evaluation model. This method not only can exert the unique advantages of BP neural network, but also overcome the difficulty of seeking the high grade training sample data. The agricultural information degree evaluation of 10 cities in Jilin province indicates that the method to evaluate the agricultural information degree is stable and reliable.
Citation:
Zhibin Liu, Li Bai, "The BP Neural Network Optimizing Design Model for Agricultural Information Measurement Based on Multistage Dynamic Fuzzy Evaluation," wkdd, pp.68-71, First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008), 2008
Usage of this product signifies your acceptance of the Terms of Use.