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  1. 1

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

    Published 2020
    “…Performance results show that the MADE algorithm based on lead-acid battery has a high level of LLP and minimum cost among other types of storage batteries. …”
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    Thesis
  2. 2

    Software defect prediction framework based on hybrid metaheuristic optimization methods by Wahono, Romi Satria

    Published 2015
    “…The proposed framework and models that are are considered to be the specific research contributions of this thesis are: 1) a comparison framework of classification models for software defect prediction known as CF-SDP, 2) a hybrid genetic algorithm based feature selection and bagging technique for software defect prediction known as GAFS+B, 3) a hybrid particle swarm optimization based feature selection and bagging technique for software defect prediction known as PSOFS+B, and 4) a hybrid genetic algorithm based neural network parameter optimization and bagging technique for software defect prediction, known as NN-GAPO+B. …”
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    Thesis
  3. 3

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…However, the classification accuracy and computational cost are not satisfied. In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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    Thesis
  4. 4

    The development of deformable bodies collision response algorithm for interactive virtual environment by Mohd. Shuaib, Norhaida, Bade, Abdullah, Daman, Daut, Sunar, Mohd. Shahrizal

    Published 2006
    “…It is an optimization algorithm that selects small areas for deformation processing based on equilibrium state. …”
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    Monograph
  5. 5

    A comparative study of multi-objective optimal power flow based on particle swarm, evolutionary programming, and genetic algorithm by Kahourzade, S., Mahmoudi, A., Mokhlis, Hazlie

    Published 2015
    “…This paper compares the performance of three population-based algorithms including particle swarm optimization (PSO), evolutionary programming (EP), and genetic algorithm (GA) to solve the multi-objective optimal power flow (OPF) problem. …”
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    Article
  6. 6

    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

    Published 2012
    “…GA is a widely used optimization algorithm based on the concept of survival of the fittest. …”
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    Thesis
  7. 7

    Imposed weighting factor optimization method for torque ripple reduction of IM fed by indirect matrix converter with predictive control algorithm by Uddin, M., Mekhilef, Saad, Rivera, M., Rodriguez, J.

    Published 2015
    “…The predictive control algorithm selects the optimum switching state that minimizes a cost function based on optimized weighting factor to actuate the indirect matrix converter. …”
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    Article
  8. 8

    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    Published 2019
    “…In fact a data clustering method is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on our proposed algorithm; which is Enhanced Binary Particle swarm Optimization (EBPSO), (ii) To mine data using various data chunks (windows) and overcome a failure of single clustering. …”
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    Thesis
  9. 9

    Proportional-integral control optimization using imperialist competitive algorithm by Soheilirad, Mohammadsoroush

    Published 2012
    “…In this dissertation, an attempt has been made to design and implement the PID Controllers by employing the Imperialist Competitive Algorithm (ICA) technique as well as the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO) algorithm, for a selected plant. …”
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    Thesis
  10. 10
  11. 11

    Harmony search-based robust optimal controller with prior defined structure by Rafieishahemabadi, Ali

    Published 2013
    “…In this approach, a combination of interacting two levels HS optimization algorithm is presented. In the first level, a new method for analytical formulation of integral square error cost function based on controller variables is elaborated for performance evaluation purposes by the proposed optimization algorithm. …”
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    Thesis
  12. 12

    A review of crossover methods and problem representation of genetic algorithm in recent engineering applications by Zainuddin, Farah Ayiesya, Abd Samad, Md Fahmi

    Published 2020
    “…Genetic algorithm (GA) is a popular technique of optimization that is bio-inspired and based on Charles Darwin's proposed principles of natural genetics and natural selection theories. …”
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    Article
  13. 13

    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

    Published 2023
    “…Moreover, K-Nearest Neighbor (KNN) classifier was used to evaluate the effectiveness of the features identified by the proposed SCSO algorithm. The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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    Article
  14. 14

    Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty by Liu, Lihua

    Published 2024
    “…Further more, an improved non-dominated sorting genetic algorithm with an elite strategy II (IMNSGA-II) has been developed to solve the two bi-objective models, surpassing existing literature’s algorithms such as Pareto Envelope-based Selection Algorithm II (PESA-II) and NSGA-II. …”
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    Thesis
  15. 15

    Optimization of Machining Parameters in Turning Operation Using PSO and AIS Algorithms: A Survey by Abbas, Adnan Jameel, Minhat, Mohamad, Abd Rahman, Md Nizam

    Published 2012
    “…This study deals with different machining performance in turning operation like surface roughness, material removal rate , tool wear , tool life, production cost, machining time and cutting temperature. Most papers in the field of turning parameters optimization are based on (PSO) algorithms, but only a few efforts that are using (AIS) algorithms. …”
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    Article
  16. 16

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

    Published 2024
    “…This research aims to develop a scheme based on a feedforward neural network (FNN) with a vectorized algorithm (FNNVA) for solving FDEs in the Caputo sense (FDEsC) using selected first-order optimization techniques: simple gradient descent (GD), momentum method (MM), and adaptive moment estimation method (Adam). …”
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    Thesis
  17. 17

    Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

    Published 2008
    “…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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    Undergraduates Project Papers
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    Scaled Conjugate Gradient using strong Wolfe line search for portfolio selection / Nurfatihah Anizan by Anizan, Nurfatihah

    Published 2024
    “…Based on the results, the Scaled LAMR method is the most robust method among others as it can solve 100% of the test functions. …”
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    Thesis
  20. 20

    A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition by Koh J.S., Tan R.H.G., Lim W.H., Tan N.M.L.

    Published 2024
    “…Finally, a modified local search method using Perturb and Observe with adaptive step size method (P&O-ASM) is proposed to refine the near-optimal duty cycle and track GMPP with negligible oscillations. …”
    Article