Enhancing extreme learning machines classification with moth-flame optimization technique

• Main Authors: Alade, Oyekale Abel, Sallehuddin, Roselina, Mohamed Radzi, Nor Haizan
• Format: Article
• Language: English
• Published: Institute of Advanced Engineering and Science 2022
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/98678/1/RoselinaSallehuddin2022_EnhancingExtremeLearningMachines.pdf; http://eprints.utm.my/id/eprint/98678/; http://dx.doi.org/10.11591/ijeecs.v26.i2.pp1027-1035
• Institution: Universiti Teknologi Malaysia

Extreme learning machine (ELM) algorithm assigns the input weights and biases in a "one-time stamp" fashion, this method makes the algorithm to be ill-conditioned and reduces its classification accuracy. The contribution of this work is the enhancement of the performance of ELM with the mo...