RETRACTED ARTICLE: Instant coffee classification by electronic noses

Abstract

Normally, an electronic nose project uses two researches areas which are hardware for developing sensors to detect substance smell and software using pattern matching theorem for recognizing substance. For this research, the operation begins with sensors hit the coffee smell. The result is converted from analog to digital representation. An artificial intelligence is a tool of a thinking system which can create knowledge as if a human does. The objective of this research is to classify instant coffee by using electronic noses. We used eight types of coffee in Thailand market for this project which are 1) Moccona-select, 2) Moccona-royal gold, 3) Nescafe redcup, 4) Nescafe gold, 5) Khao Shong brown, 6) Khao Shong red, 7) Oem-Big C and 8) Superclass. We compared four structures of neural network to classify the coffee data. The precision of correctness is equal to 65.63 for a neural network structure as 7 input-layer nodes, 14 hidden-layerl nodes, 48 hidden-layer2 nodes and 8 output-layer nodes. © 2010 IEEE.