Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Keem Siah Yap"'
Publikováno v:
IEEE Access, Vol 8, Pp 28934-28946 (2020)
In near decades machine learning approaches have received overwhelming attention from many researchers for solving problems that cannot be ironed out by traditional approaches. However, most of these approaches produces output that is not equivalent
Externí odkaz:
https://doaj.org/article/6c471b789f4745448f05cbebd5d1dadd
Publikováno v:
IEEE Access, Vol 8, Pp 163026-163043 (2020)
Extreme Learning Machine improved the iterative procedures of adjusting weights by randomly selecting hidden neurons besides analytically determining the output weights. In this paper, the basic ELM neural network was enhanced with a simplified netwo
Externí odkaz:
https://doaj.org/article/45e84656e91f4c44a8c22b63e444374d
Realization of a Hybrid Locally Connected Extreme Learning Machine With DeepID for Face Verification
Publikováno v:
IEEE Access, Vol 7, Pp 70447-70460 (2019)
Most existing state-of-the-art deep learning algorithms discover sophisticated representations in huge datasets using convolutional neural networks (CNNs) that mainly adopt backpropagation (BP) algorithm as the backbone for training the face recognit
Externí odkaz:
https://doaj.org/article/a8d0571ad64543b093c2400f188d10db
Publikováno v:
IEEE Access, Vol 7, Pp 116438-116452 (2019)
The Generalized Adaptive Resonance Theory (GART) model is a supervised online learning neural network based on an integration of Adaptive Resonance Theory (ART) and the Generalized Regression Neural Network (GRNN). It is capable of online learning, a
Externí odkaz:
https://doaj.org/article/fa62bc4f15b34f948f900e03e219101d
Publikováno v:
Soft Computing. 25:11209-11233
In recent decades, researches on optimizing the parameter of the artificial neural network (ANN) model has attracted significant attention from researchers. Hybridization of superior algorithms helps improving optimization performance and capable of
Autor:
Waraporn Fangrit, Keem Siah Yap, Mukhtar Fatihu Hamza, Shen Yuong Wong, Siow-Wee Chang, Hwa Jen Yap
Publikováno v:
Intelligent Decision Technologies. 14:493-506
Flexible flow shop is becoming more interested and applied in industries due to its impact from higher workloads. Flexible flow shop scheduling problem is focused to minimize the makespan. A metaheuristic model based on Hybrid Tabu Search is develope
Publikováno v:
IEEE Access, Vol 8, Pp 28934-28946 (2020)
In near decades machine learning approaches have received overwhelming attention from many researchers for solving problems that cannot be ironed out by traditional approaches. However, most of these approaches produces output that is not equivalent
Autor:
Hui Jing Lee, Mansur Mohammed Ali Gamel, Pin Jern Ker, Md Zaini Jamaludin, Yew Hoong Wong, Keem Siah Yap, Jon R. Willmott, Matthew J. Hobbs, John. P.R. David, Chee Hing Tan
Publikováno v:
Materials Science in Semiconductor Processing. 153:107135
Publikováno v:
Journal of Physics: Conference Series. 2319:012004
When there is a contingency in a major transmission system, it is crucial to locate and detect abnormal parameters using an accurately modeled gas turbine (GT) generator. In this paper, a new method was proposed to model, a GT generator system. First
Fault Diagnosis in Wind Energy Management System using Extreme Learning Machine: A Systematic Review
Publikováno v:
Journal of Physics: Conference Series. 2319:012014
Fault diagnosis is increasingly important given the worldwide demand on wind energy as one of the promising renewable energy sources. This systematic review aimed to summarize the fault diagnosis using Extreme Learning Machine (ELM) on wind energy. F