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  1. 1

    Performance of Multi-Layer Perceptron Neural Networks with an Exponential Decay Activation Function in Airwaves Estimation by Muhammad , Abdulkarim, Wan Ahmad, Wan Fatimah, Shafie, Afza, Razali, Radzuan

    Published 2013
    “…The benchmark for the performance evaluation is by comparing the exponential decay activation function with log-sigmoid and tan-sigmoid activation functions through back propagation algorithm. …”
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    Citation Index Journal
  2. 2

    Modeling the prediction of hydrogen production by co-gasification of plastic and rubber wastes using machine learning algorithms by Ayodele B.V., Mustapa S.I., Kanthasamy R., Zwawi M., Cheng C.K.

    Published 2023
    “…Chemical activation; Gasification; Learning algorithms; Machine learning; Multilayer neural networks; Neurons; Plastics industry; Predictive analytics; Rubber; Rubber industry; Activation functions; MLP neural networks; Model architecture; Multi layer perceptron; Neural network algorithm; Optimized performance; Process operation; Radial Basis Function(RBF); Hydrogen production…”
    Article
  3. 3

    Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations by Hossain, S.K.S., Ayodele, B.V., Alhulaybi, Z.A., Alwi, M.M.A.

    Published 2022
    “…The RBFNN model with softmax as the hidden layer activation function and identity as the outer layer activation function has the least predictive performance, as indicated by an R2 of 0.403 and a RMSE of 301.55. …”
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    Article
  4. 4

    Effort Estimation Model for Function Point Measurement by Koh, Tieng Wei

    Published 2007
    “…The process starts with the planning phase activities and refined throughout the development. …”
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    Thesis
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    SUDOKU HELPER by Abdul Razak, Muhammad Asyraf

    Published 2015
    “…In this paper research, author presents an algorithm to provide a tutorial for any Sudoku player who got stuck during the solving process. …”
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    Final Year Project
  7. 7

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…The uniqueness of this approach lies in embedding an integrated scheduling function into a partially integrated process planning function in order to exploit the strategic potentials of flexibility and reconfigurability in manufacturing systems. …”
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    Thesis
  8. 8

    A Hybrid Active Contour and Artificial Bee Colony Algorithm for Segmenting Mixed-Meal Food Images (S/O: 13239) by Harun, Nor Hazlyna, Mahmuddin, Massudi, Harun, Hazaruddin

    Published 2020
    “…In addition, a modified active contour method is presented in this paper using the artificial bee colony (ABC) algorithm to optimize the weights of the external energy function in the original active contour (AC) method. …”
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    Monograph
  9. 9

    Modelling of biogas production process with evolutionary artificial neural network and genetic algorithm by Fakharudin, Abdul Sahli

    Published 2017
    “…The EANN used a modified activation function to meet the optimisation requirement. …”
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    Thesis
  10. 10

    Real time nonlinear filtered-x lms algorithm for active noise control by Sahib, Mouayad Abdulredha

    Published 2012
    “…The NLFXLMS algorithm is a stochastic gradient algorithm that incorporates the derivative of a nonlinear plant model which is represented by the scaled error function (SEF) in the controller design. …”
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    Thesis
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  12. 12

    Jogging activity recognition using k-NN algorithm by Afifah Ismail

    Published 2022
    “…The objective of this project are 1) to investigate human activity recognition (HAR) for jogging activity and k-Nearest Neighbors (k-NN) algorithm for jogging classifier, 2) to apply HAR AND k-NN for jogging recognition and classification and, 3) to test the functionality of the k-NN algorithm of jogging recognition and classification. …”
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    Academic Exercise
  13. 13

    The effect of adaptive parameters on the performance of back propagation by Abdul Hamid, Norhamreeza

    Published 2012
    “…The activation functions are adjusted by the adaptation of gain parameters together with adaptive momentum and learning rate value during the learning process. …”
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    Thesis
  14. 14

    DEVELOPMENT OF A MULTI-OBJECTIVE OPTIMZATION FRAMEWORK FOR INDUSTRIAL PROCESSES by GANESAN, TIMOTHY

    Published 2014
    “…The proposed framework is introduced as the 'surgery framework (SF)' since its prime functionality is to dissect the algorithm and add certain mechanisms into it. …”
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    Thesis
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    Loudspeaker nonlinearity compensation with inverse tangent hyperbolic function-based predistorter for active noise control by Sahib, Mouayad Abdulredha, Raja Ahmad, Raja Mohd Kamil

    Published 2014
    “…In active noise control (ANC), the performance of the filtered-x least mean squares (FXLMS) algorithm is degraded by the saturation of the loudspeaker in the secondary path. …”
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    Article
  17. 17

    An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

    Published 2014
    “…Most of the training algorithms focus on weight values, activation functions, and network structures for providing optimal outputs. …”
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    Thesis
  18. 18

    Parametric modelling of twin rotor system using chaotic fractal search algorithm by Tuan Abdul Rahman, Tuan Ahmad Zahidi

    Published 2016
    “…The final results found that Chaotic Fractal Search (CFS) algorithm with Gauss/Mouse map shows superiority over other enhanced SFS algorithms when applied both in Diffusion Process and Updating Process.…”
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    Conference or Workshop Item
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    A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds by Salim, Naomie, Shah, J. Z.

    Published 2007
    “…In this work a fuzzy hierarchical algorithm is developed which provides a mechanism not only to benefit from the fuzzy clustering process but also to get advantage of the multiple membership function of the fuzzy clustering. …”
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    Book Section