Search Results - "Siah Yap, Keem"

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  1. 1

    Extreme Learning Machines: A new approach for prediction of reference evapotranspiration by Abdullah, Shafika Sultan, Malek, M.A., Abdullah, Namiq Sultan, Kisi, Ozgur, Yap, Keem Siah

    Published in Journal of hydrology (Amsterdam) (01-08-2015)
    “…•ELM model is proposed for prediction of ET0 in Iraq.•The ELM is more efficient than FFBP model.•The proposed ELM is efficient in predicting ET0 with complete…”
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    Journal Article
  2. 2

    On Equivalence of FIS and ELM for Interpretable Rule-Based Knowledge Representation by Wong, Shen Yuong, Yap, Keem Siah, Yap, Hwa Jen, Tan, Shing Chiang, Chang, Siow Wee

    “…This paper presents a fuzzy extreme learning machine (F-ELM) that embeds fuzzy membership functions and rules into the hidden layer of extreme learning machine…”
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    Journal Article
  3. 3

    Nontechnical Loss Detection for Metered Customers in Power Utility Using Support Vector Machines by Nagi, J., Yap, K.S., Sieh Kiong Tiong, Ahmed, S.K., Mohamad, M.

    Published in IEEE transactions on power delivery (01-04-2010)
    “…Electricity consumer dishonesty is a problem faced by all power utilities. Finding efficient measurements for detecting fraudulent electricity consumption has…”
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    Journal Article
  4. 4

    Advances of metaheuristic algorithms in training neural networks for industrial applications by Chong, Hue Yee, Yap, Hwa Jen, Tan, Shing Chiang, Yap, Keem Siah, Wong, Shen Yuong

    Published in Soft computing (Berlin, Germany) (01-08-2021)
    “…In recent decades, researches on optimizing the parameter of the artificial neural network (ANN) model has attracted significant attention from researchers…”
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    Journal Article
  5. 5

    Improving SVM-Based Nontechnical Loss Detection in Power Utility Using the Fuzzy Inference System by Nagi, J, Keem Siah Yap, Sieh Kiong Tiong, Ahmed, S K, Nagi, F

    Published in IEEE transactions on power delivery (01-04-2011)
    “…This letter extends previous research work in modeling a nontechnical loss (NTL) framework for the detection of fraud and electricity theft in power…”
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    Journal Article
  6. 6

    A Constrained Optimization based Extreme Learning Machine for noisy data regression by Yuong Wong, Shen, Siah Yap, Keem, Jen Yap, Hwa

    Published in Neurocomputing (Amsterdam) (01-01-2016)
    “…Most of the existing Artificial Intelligence (AI) models for data regression commonly assume that the data samples are completely clean without noise or worst…”
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    Journal Article
  7. 7

    A New Probabilistic Output Constrained Optimization Extreme Learning Machine by Wong, Shen Yuong, Yap, Keem Siah, Li, Xiao Chao

    Published in IEEE access (2020)
    “…In near decades machine learning approaches have received overwhelming attention from many researchers for solving problems that cannot be ironed out by…”
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    Journal Article
  8. 8

    Realization of a Hybrid Locally Connected Extreme Learning Machine With DeepID for Face Verification by Wong, Shen Yuong, Yap, Keem Siah, Zhai, Qingwei, Li, Xiaochao

    Published in IEEE access (2019)
    “…Most existing state-of-the-art deep learning algorithms discover sophisticated representations in huge datasets using convolutional neural networks (CNNs) that…”
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    Journal Article
  9. 9

    Daily maximum load forecasting of consecutive national holidays using OSELM-based multi-agents system with weighted average strategy by Siah Yap, Keem, Jen Yap, Hwa

    Published in Neurocomputing (Amsterdam) (01-04-2012)
    “…In the previous research, a Multi-Agent System based on Online Sequential Extreme Learning Machine (OSELM) neural network and Bayesian Formalism (MAS-OSELM-BF)…”
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    Journal Article
  10. 10

    Application of Fuzzy Inference Rules to Early Semi-automatic Estimation of Activity Duration in Software Project Management by Chin Hooi Tan, Keem Siah Yap, Ishibuchi, Hisao, Nojima, Yusuke, Hwa Jen Yap

    Published in IEEE transactions on human-machine systems (01-10-2014)
    “…Expert judgment is widely used for activity duration estimation in software project management. While there are both advantages and disadvantages of expert…”
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    Journal Article
  11. 11

    Enhancement of Neural Network Based Multi Agent System for Classification and Regression in Energy System by Yaw, Chong Tak, Yap, Keem Siah, Wong, Shen Yuong, Yap, Hwa Jen, Paw, Johnny Koh Siew

    Published in IEEE access (2020)
    “…Extreme Learning Machine improved the iterative procedures of adjusting weights by randomly selecting hidden neurons besides analytically determining the…”
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    Journal Article
  12. 12

    Hybrid Data Regression Model Based on the Generalized Adaptive Resonance Theory Neural Network by Wong, Shen Yuong, Yap, Keem Siah, Lim, Chee Peng, Lee, Eric Wai Ming

    Published in IEEE access (2019)
    “…The Generalized Adaptive Resonance Theory (GART) model is a supervised online learning neural network based on an integration of Adaptive Resonance Theory…”
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    Journal Article
  13. 13

    Compressing and improving fuzzy rules using genetic algorithm and its application to fault detection by Keem Siah Yap, Sheng Yuong Wong, Sheih Kiong Tiong

    “…The fuzzy rule sets, which have been derived from the hybrid neural network model, called the O-EGART-PR-FIS, is an integration of the Adaptive Resonance…”
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    Conference Proceeding
  14. 14

    MOSELM approach for Voltage Stability Indicator using phasor measurement units by Abidin, I. Z., Keem Siah Yap, Saadun, N., Abdullah, S. K. S., Mohd Sarmin, M. K. N.

    “…Voltage stability assessment is important in order to ensure a stable power system. Two algorithms were discussed in this paper which looks into estimating…”
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    Conference Proceeding
  15. 15

    A computational intelligence scheme for the prediction of the daily peak load by Nagi, Jawad, Yap, Keem Siah, Nagi, Farrukh, Tiong, Sieh Kiong, Ahmed, Syed Khaleel

    Published in Applied soft computing (01-12-2011)
    “…Forecasting of future electricity demand is very important for decision making in power system operation and planning. In recent years, due to privatization…”
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    Journal Article
  16. 16

    Improved GART Neural Network Model for Pattern Classification and Rule Extraction With Application to Power Systems by Yap, Keem Siah, Lim, Chee Peng, Au, Mau Teng

    Published in IEEE transactions on neural networks (01-12-2011)
    “…Generalized adaptive resonance theory (GART) is a neural network model that is capable of online learning and is effective in tackling pattern classification…”
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    Journal Article
  17. 17

    A new multi agent system based on online sequential extreme learning machines and Bayesian Formalism by Keem Siah Yap

    “…In this article, a new Multi Agent System based on Online Sequential Extreme Learning Machine (OSELM) neural network and Bayesian Formalism (MAS-OSELM-BF) is…”
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    Conference Proceeding
  18. 18

    A new hybrid fuzzy ARTMAP and radial basis function neural network with online pruning strategy by Shoun Ying Leow, Shen Yuong Wong, Keem Siah Yap, Hwa Jen Yap

    “…In this paper, a new online learning algorithm is proposed to learn a data sample in hybrid mode. This new algorithm is developed and referred as Growing and…”
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    Conference Proceeding
  19. 19

    Application of genetic algorithm for fuzzy rules optimization on semi expert judgment automation using Pittsburg approach by Tan, Chin Hooi, Yap, Keem Siah, Yap, Hwa Jen

    Published in Applied soft computing (01-08-2012)
    “…[Display omitted] ► This paper presents the optimization of fourteen fuzzy rules for semi expert judgment automation in software project management. ► The goal…”
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    Journal Article
  20. 20

    A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification by Wong, Shen Yuong, Yap, Keem Siah, Yap, Hwa Jen, Tan, Shing Chiang

    Published in Neural processing letters (01-12-2015)
    “…This paper presents a Hybrid Fuzzy ARTMAP (FAM) and Online Extreme learning machine (OELM), hereafter denoted as FAM-OELM, which enables online learning to…”
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    Journal Article