Notice of RetractionInstant coffee classification by electronic noses

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

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-layer1 nodes, 48 hidden-layer2 nodes and 8 output-layer nodes.