Title :
The application research of improving neural network algorithm in the grain monitoring
Author :
JianJun, Wu ; Biao, Bao Zhan
Author_Institution :
Sch. of Comput. Sci. & Technol., Wuhan Univ. of Technol., Zhengzhou, China
Abstract :
In allusion to the insufficiencies such as knowledge acquirement, reasoning ability and self-learning ability, the paper applies neural network into expert system, combines with the system of measurement and control for grain storage, and puts forward an improved BP algorithm. This algorithm does not need the prior hypothesis model and has a good compatibility to the complete and noisy information; it also can solve the non-linear problem well. This new algorithm has coordinated contradictions between learning efficiency and convergence rate and improved skilled speed and convergence rate. From the results of experiment, we can see that the new algorithm has some advantages, such as quickly, validity and practicability.
Keywords :
agricultural products; agriculture; backpropagation; computerised monitoring; convergence; expert systems; neural nets; BP algorithm; convergence rate; expert system; grain monitoring; grain storage control; hypothesis model; neural network algorithm; nonlinear problem; Convergence; Coordinate measuring machines; Monitoring; BP algorithm; expert system; measurement and control for grain storage; neural network;
Conference_Titel :
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6539-2
DOI :
10.1109/ICACTE.2010.5579836