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Mohammadigol R, khoshtaghaza M H, Malekfar R, Mirabolfathi M, Nikbakht A M, Darabi H. Evaluation of artificial neural networks(MLP) performance in biologic samples Raman spectra classification Detection of the aflatoxin in pistachio. ICOP & ICPET _ INPC _ ICOFS 2014; 20 :1017-1020
URL: http://opsi.ir/article-1-407-en.html
URL: http://opsi.ir/article-1-407-en.html
Reza Mohammadigol *1 
, Mohammad hadi Khoshtaghaza , Rasoul Malekfar , Mansoure Mirabolfathi , Ali mohammad Nikbakht , Hadi Darabi
, Mohammad hadi Khoshtaghaza , Rasoul Malekfar , Mansoure Mirabolfathi , Ali mohammad Nikbakht , Hadi Darabi
Abstract: (5861 Views)
Abstract- The objective of this study was to detect aflatoxin contamination in pistachio applying Raman spectroscopy technique and artificial neural networks. After spectra acquisition considering to principal components analysis(PCA)results, Second Derivative preprocessing method was selected and then principal components(PCs) were extracted to reduce the data dimensions. To classify samples, two kind of Multilayer perseptron feed forward back propagation topologies (including 8 neurons in hidden layer as first one and including 2 and 4 neurons in the first and second hidden layers respectively as a second one) were used. On average our classifiers performed with 92(one layer ANN) and 82(two layers ANN) percent accuracy . Both classifiers performance, for no contaminated samples recognition (as they achieved to 100 percent accuracy) was successful.
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