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Classification of aromatic herbs using artificial intelligent technique


Che Soh, Azura and Mohamad Yusof, Umi Kalsom and Mohamad Radzi, Nur Fadzilah and Ishak, Asnor Juraiza and Hassan, Mohd Khair (2017) Classification of aromatic herbs using artificial intelligent technique. Pertanika Journal of Science & Technology, 25 (spec. Jan.). pp. 119-128. ISSN 0128-7680; ESSN: 2231-8526

Abstract / Synopsis

Herbs have unique characteristics such as colour, texture and odour. In general, herb identification is through organoleptic methods and is heavily dependent on botanists. It is becoming more difficult to identify different herb species in the same family based only on their aroma. It is because of their similar physical appearance and smell. Artificial technology, unlike humans, is thought to have the capacity to identify different species with precision. An instrument used to identify aroma is the electronic nose. It is used in many sector including agriculture. The electronic nose in this project was to identify the odour of 12 species such as lauraceae, myrtaceae and zingiberaceae families. The output captured by the electronic nose gas sensors were classified using two types of artificial intelligent techniques: Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS). From the result, ANFIS has 94.8% accuracy compared with ANN at 91.7%.

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Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
Publisher: Universiti Putra Malaysia Press
Keywords: Artificial neural network; Adaptive neuro-fuzzy inference system
Depositing User: Nabilah Mustapa
Date Deposited: 30 Jun 2017 17:45
Last Modified: 05 Jul 2017 12:57
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