Title :
Based on transcendental knowledge of neuron model to achieve PH detection and control
Author :
Chi, Tao ; Chen, Ming
Author_Institution :
Coll. of Inf. Technol., Shanghai Ocean Univ., Shanghai, China
fDate :
June 29 2010-July 1 2010
Abstract :
In the environment inspection and control process, there are some problems that can´t be solved because of the lack of background knowledge, but artificial neural network system can learn to deal with these problems by learning specific examples and give good answer. In view of the highly non-linear and changeable problems existing in the PH neutralization, the paper proposed completing the PH value examination and the control operation which based on transcendental knowledge with the union neuron control, and analyzed the reason why PH value sometimes is able to have the oscillatory occurrences. The experiment proved that this method may effectively control the neutralization processes which have the serious nonlinear response property. By means of adjusting neuron gain, it eliminated and reduced the object which had non-linearity and non-determinacy that had the adverse effect to the neuron study and has satisfied the control request in PH neutralization process.
Keywords :
inspection; neurocontrollers; pH control; time-varying systems; PH control; PH detection; PH neutralization; artificial neural network system; control process; environment inspection; learning; neuron model; nonlinear response; oscillatory occurrences; transcendental knowledge; union neuron control; Fuzzy Rules; Neural Network; Pattern Recognition; Time-Variable Nonlinearity;
Conference_Titel :
Communication Systems, Networks and Applications (ICCSNA), 2010 Second International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-7475-2
DOI :
10.1109/ICCSNA.2010.5588710