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The BP Neural Network Optimizing Design Model for Agricultural Information Measurement Based on Multistage Dynamic Fuzzy Evaluation

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2 Author(s)
Zhibin Liu ; North China Electr. Power Univ., Baoding ; Li Bai

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 ofBP 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.

Published in:

Knowledge Discovery and Data Mining, 2008. WKDD 2008. First International Workshop on

Date of Conference:

23-24 Jan. 2008