CHEMICAL SUBSTANCE CLASSIFICATION BY ELECTRONIC NOSES
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. The operation begins with sensors hit the smell of chemical substance. 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 chemical substance by using electronic noses. We used eight types of chemical substance in the experiment which are 1) Acetone, 2) Benzene, 3) Propanal, 4) Butanol, 5) Chloroform, 6) Ethanol,7) Methane and 8) Tetrahydrofuran. We compared nine structures of neural network to classify the chemical substance data. The precision of correctness is equal to 94.64 for a neural network structure as 54 input-layer nodes, 216 hiddenlayer1 nodes, 8 hidden-layer2 nodes and 8 outputlayer nodes.
Electronic Noses Chemical substance Classification Neural Network
Chomtip Pornpanomchai Piyorot Khongchuay
Department of Computer Science, Faculty of Science Rama 6 Road, Rajchatawee, Bangkok 10400, Thailand
国际会议
北京
英文
68-72
2009-08-08（万方平台首次上网日期，不代表论文的发表时间）