Classification of n-butanol concentrations with k-NN algorithm and ANN in electronic nose

Electronic nose (e-nose) is a machine used for sensing and recognizing odors by using chemical sensors. E-nose has wide fields of applications and it is used for sensing special odors. Also performance of e-nose depends on choosing correct sensor and choosing correct pattern recognition algorithm according to field of application and kinds of odors. In this study, different n-butanol concentrations sensed by 12 metal oxide gas sensors are classified by using artificial neural network (ANN) and k-nearest neighbor (k-NN) algorithm. 100% success rate is obtained with k-NN classifier for this application. Simultaneously results of k-NN classifier are compared with ANN results. To recognize the different concentrations of n-butanol sample which is component of farm odors is first stage of the study. Advanced stage of the study recognizes the farm odors.