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  1. 1

    An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem by S. W. Su, Stephanie, Kek, Sie Long

    Published 2021
    “…,e results show that the rate of convergence of the Adam algorithm is significantly enhanced by using the AdamSE algorithm. …”
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    Article
  2. 2

    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
    “…Algorithms used to solve these problems are expected to satisfy the objectives consistently and since time translates into cost, must also be fast. …”
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    Monograph
  3. 3

    Enhancing the cuckoo search with levy flight through population estimation by Mohd Nawi, Nazri, Shahuddin, Shah Liyana, Rehman, Muhammad Zubair, Khan, Abdullah

    Published 2016
    “…This paper proposed the use of population estimation in a new meta-heuristic called Cuckoo search (CS) algorithm to minimize the training error, achieve fast convergence rate and to avoid local minimum problem. …”
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    Article
  4. 4

    Cutting temperature and surface roughness optimization in CNC end milling using multi objective genetic algorithm by Al Hazza, Muataz, Adesta, Erry Yulian Triblas, Superianto, M. Y., Riza, Muhammad

    Published 2012
    “…Due to complexity of this machining optimization problem, a multi objective genetic algorithm (MOGA) has been applied to resolve the problem, and the results have been analyzed…”
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    Proceeding Paper
  5. 5

    Compressed Sensing Implementations For Sparse Channel Estimation In OFDM Systems by Uwaechia, Anthony Ngozichukwuka

    Published 2018
    “…By using the restricted isometry property, the theoretical analysis of both CoFA and SdMP algorithms and the sufficient conditions for realizing an improved reconstruction performance were presented. …”
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    Thesis
  6. 6

    Machine failure prediction technique using recurrent neural network long short-term memory-particle swarm optimization algorithm by Rashid, N.A., Abdul Aziz, I., Hasan, M.H.B.

    Published 2019
    “…This paper proposes a hybrid prediction technique based on Recurrent Neural Network Long-Short-Term Memory (RNN-LSTM) with the integration of Particle Swarm Optimization (PSO) algorithm to estimate the Remaining Useful Life (RUL) of machines. …”
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    Article
  7. 7

    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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    Thesis
  8. 8

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
    Article
  9. 9

    Feedforward neural network for solving particular fractional differential equations by Admon, Mohd Rashid

    Published 2024
    “…The final scheme utilizes a two hidden layer FNNVA, with Adam optimization, using suitable number of nodes and value of learning rates to handle problems involving memory and fractal concepts. …”
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    Thesis
  10. 10

    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

    Published 2020
    “…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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    Thesis
  11. 11

    Ant colony optimization and genetic algorithm models for suspended sediment discharge estimation for gorgan-river, Iran by Mohammad Reza Pour, Omolbani

    Published 2011
    “…New models based on artificial intelligence models, namely; Ant Colony Optimization (ACO) and Genetic Algorithm (GA) are now being used more frequently to solve optimization problems. …”
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    Thesis
  12. 12

    Algorithm of local features fusion and modified covariance-matrix technique for hand motion position estimation and hand gesture trajectory tracking approach by Thabet, Eman, Khalid, Fatimah, Sulaiman, Puteri Suhaiza, Yaakob, Razali

    Published 2020
    “…As a result, the proposed approach has shown adorable optimization achieving an accuracy rate of 96.97%, overcoming the problems of hand appearance variation in the complicated environment.…”
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    Article
  13. 13

    Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques by Salami, Momoh Jimoh Emiyoka, Sidek, Shahrul Na'im

    Published 2003
    “…In this method of analysis the exponential signal is converted to a convolution model whose input is a train of weighted delta function that contains the signal parameters to be determined.The resolution of the estimated decay rates is poor if the conventional fast Fourier transform (FFT) algorithm is used to analyse the resulting deconvolved data. …”
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    Article
  14. 14

    Determination Of Heat Transfer Coefficients In Heat Exchangers By Genetic Algorithm by Tan Boon Tat, Boon Tat

    Published 2010
    “…In particular, GA is being extensively used in the field of optimization. This paper discusses the utilization of GA in estimating the coefficients and exponents in developing the Nusselt Number correlation in two different heat exchanger geometries, with the aim to reduce the error incurred in predicting heat transfer coefficients and heat transfer rates. …”
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    Final Year Project
  15. 15

    Estimating Missing Precipitation to Optimize Parameters for Prediction of Daily Water Level Using Artificial Neural Network by Dayang Suhaila, Awang Suhaili

    Published 2006
    “…The back propagation algorithm was adopted for this study. The optimal model for predicting missing data found in this study is the network with the combination of learning rate and the number of neurons in the hidden layer of 0.2 and 60. …”
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    Final Year Project Report / IMRAD
  16. 16

    Using genetic algorithms to optimise land use suitability by Pormanafi, Saeid

    Published 2012
    “…The third objective is to optimize the land use map using economic benefits. …”
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    Thesis
  17. 17

    Robust estimation methods for fixed effect panel data model having block-concentrated outliers by Abu Bakar @ Harun, Nor Mazlina

    Published 2019
    “…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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    Thesis
  18. 18

    Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation by Rahimizadeh, Hamid

    Published 2009
    “…In this study a decision boundary equation, which is acquired from class conditional probability density function (PDF) of colors, based on Bayes decision theory has been used for desired color segmentation. The estimation of unknown PDF is a common problem and in this study Gaussian kernel function which is most widely used nonparametric density estimation method has been used for PDF calculation. …”
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    Thesis
  19. 19

    Implementation of Symmetric Rank-One Methods for Unconstrained Optimization by Khiyaban, Farzin Modarres

    Published 2010
    “…A review of di®erent minimization methods that can be used to solve unconstrained optimization problems is also given. …”
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    Thesis
  20. 20

    Sizing and placement of battery-coupled distributed photovoltaic generations by Ali, A., Mohd Nor, N., Ibrahim, T., Fakhizan Romlie, M.

    Published 2017
    “…Mixed-integer optimization using a genetic algorithm is employed for solving the optimization problem. …”
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    Article