Analysis of algorithms variation in multilayer perceptron neural network for agarwood oil qualities classification

• Main Authors: Nurul Shakila, Ahmad Zubir, Mohamad Aqib Haqmi, Abas, Ismail, N. A., Nor Azah, Mohd Ali, Mohd Hezri, Fazalul Rahiman, Ng, K. M., Saiful Nizam, Tajuddin
• Format: Conference or Workshop Item
• Language: English; English
• Published: IEEE 2017
• Subjects: QA Mathematics; QD Chemistry; TP Chemical technology
• Online Access: http://umpir.ump.edu.my/id/eprint/28990/1/Analysis%20of%20algorithms%20variation%20in%20multilayer%20perceptron%20neural%20network%20.pdf; http://umpir.ump.edu.my/id/eprint/28990/2/Analysis%20of%20algorithms%20variation%20in%20multilayer%20perceptron%20neural%20network_FULL.pdf; http://umpir.ump.edu.my/id/eprint/28990/; https://doi.org/10.1109/ICSGRC.2017.8070580

This study investigates the performance of the Multilayer Perceptron (MLP) classifier in discriminating the qualities of agarwood oil significant compounds by different qualities based on three training algorithms namely Scaled Conjugate Gradient (SCG), Levernbergh-Marquardt (LM) and Resilient Backp...