Title :
Software Development for Black Tea´s Physical Variable and Quality Class Relationship Analyzing Using Correlation Adaptive Vis. Pat. Recognition Artificial Neural Network Based Expert System: Proof of Concept of Auto Parameter Choosing Expert System
Author :
Jenie, Renan Prasta
Author_Institution :
Inf. Technol. Directorate, Technol. Dev. Div., Bina Nusantara Univ., Jakarta, Indonesia
Abstract :
The absence of standard in black tea assessment was one main obstacle in its quality assurance. This research were contains process of black tea assessment software development, software problem solving concept, and the software evaluation made. This paper was a proof of simple concept that an expert system should automatically find and chose relevant parameters from relationship between raw image data and custom customer classification system, not only measuring dictated parameter and calculate the result on it.
Keywords :
beverage industry; expert systems; image recognition; neural nets; production engineering computing; software quality; artificial neural network; black tea assessment; correlation adaptive visual pattern recognition; custom customer classification system; expert system; physical variable; quality assurance; quality class relationship; software development; software evaluation; software problem solving concept; Accuracy; Arrays; Artificial neural networks; Correlation; Expert systems; Software; Testing; artificial neural network; black tea; expert system; parameter correlation analysis;
Conference_Titel :
Advances in Computing, Control and Telecommunication Technologies (ACT), 2010 Second International Conference on
Conference_Location :
Jakarta
Print_ISBN :
978-1-4244-8746-2
Electronic_ISBN :
978-0-7695-4269-0
DOI :
10.1109/ACT.2010.13