Title :
Grain Quality Evaluation Method Based on Combination of FNN Neural Networks with D-S Evidence Theory
Author :
Zhu, Yuhua ; Zhen, Tong
Author_Institution :
Coll. of Inf. Sci. & Eng., Henan Univ. of Technol., Zhengzhou, China
Abstract :
The output of the fuzzy neural network was adopted as BPAF (basic probability assignment function) in this paper. By training the fuzzy neural network, the massive language fuzzy information and the concerned expert´s experience were integrated in the decision process, it advantageous in enhancing the BPAF of the accuracy, the reliability and the objectivity. Therefore, using the superiority of D-S evidence theory in the processing uncertainty aspect and analyzing the situation of grain by FNN and the D-S evidence theory union, it can greatly decrease the uncertainty of system.
Keywords :
agricultural products; fuzzy neural nets; inference mechanisms; probability; D-S evidence theory; FNN neural network; basic probability assignment function; fuzzy neural network; grain quality evaluation; Decision making; Educational institutions; Electronic mail; Fuzzy neural networks; Humidity; Information science; Neural networks; Power system modeling; Temperature sensors; Uncertainty;
Conference_Titel :
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4507-3
Electronic_ISBN :
978-1-4244-4507-3
DOI :
10.1109/CISE.2009.5362739
