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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
    “…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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    Thesis
  2. 2

    Towards large scale unconstrained optimization by Abu Hassan, Malik

    Published 2007
    “…We also attempt to construct a new matrix-storage free which uses the SR1 update (MF-SR1). The MF-SR1 method is more superior than the MF-BFGS method in some problems. …”
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    Inaugural Lecture
  3. 3

    Quasi-Newton methods based on ordinary differential equation approach for unconstrained nonlinear optimization by Khiyabani, Farzin Modarres, Leong, Wah June

    Published 2014
    “…Fundamentally this is a gradient system based on the first order optimality conditions of the optimization problem. To further extend the methods for solving large-scale problems, a feature incorporated to the proposed methods is that a limited memory setting for matrix–vector multiplications is used, thus avoiding the computational and storage issues when computing Jacobian information. …”
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    Article
  4. 4

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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    Thesis
  5. 5

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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    Thesis
  6. 6

    Quasi-Newton type method via weak secant equations for unconstrained optimization by Lim, Keat Hee

    Published 2021
    “…In this thesis, variants of quasi-Newton methods are developed for solving unconstrained optimization problems. …”
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    Thesis
  7. 7

    State of charge estimation of lithium-ion batteries in an electric vehicle using hybrid metaheuristic - deep neural networks models by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Isuwa, Jeremiah

    Published 2025
    “…The proposed TLBO-deep neural networks (TLBO-DNNs) method was evaluated on a dataset of 1,064,000 samples, with performance assessed using mean absolute error (MAE), root mean square error (RMSE), and convergence value. …”
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    Article
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    Ethereum blockchain-based three factor authentication and multi-contract access control for secure smart home environment in 5G networks by Atiewi S., Al-Rahayfeh A., Almiani M., Abuhussein A., Yussof S.

    Published 2025
    “…To improve secure service providing, we perform the detection of malicious and vulnerable users using Improved Cuckoo Optimization and Support Vector Machine (ICO-SVM) and Gated Recurrent Unit and Residual Neural Network (GRU-ResNNet) algorithm in ROS-EB which reduces the vulnerability in the smart home. …”
    Article
  10. 10

    Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications by Hannan M.A., Faisal M., Jern Ker P., Begum R.A., Dong Z.Y., Zhang C.

    Published 2023
    “…Carbon; Decarbonization; Electric energy storage; Fossil fuels; Global warming; Renewable energy resources; Carbon emissions; Decarbonisation; Energy storage system; Method; Microgrid; Optimal energy; Optimization algorithms; Sizing; Storage systems; System sizings; Cost effectiveness…”
    Review
  11. 11

    Optimal allocation of battery energy storage system using whale optimization algorithm by Wong L.A., Ramachandaramurthy V.K.

    Published 2023
    “…Battery storage; Electric batteries; Battery energy storage systems; Firefly algorithms; Loss reduction; Meta-heuristic methods; Optimal allocation; Optimization algorithms; Overall system loss reduction; Performance; System loss; Whale optimization algorithm; Particle swarm optimization (PSO)…”
    Conference Paper
  12. 12

    Optimization algorithms for energy storage integrated microgrid performance enhancement by Roslan M.F., Hannan M.A., Ker P.J., Muttaqi K.M., Mahlia T.M.I.

    Published 2023
    “…Controllers; Electric power transmission; Electric power utilization; Energy management systems; Energy resources; Energy storage; Iterative methods; Learning algorithms; Microgrids; Operating costs; Particle swarm optimization (PSO); Scheduling; Scheduling algorithms; Stochastic systems; Storage management; Two term control systems; Charge-discharge; Day-ahead; Distributed Energy Resources; Microgrid; Optimization algorithms; Optimized controllers; Optimized scheduling; Performance enhancements; Scheduling controllers; Storage systems; Energy management…”
    Article
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    Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals by Homayouni, Seyed Mahdi

    Published 2012
    “…Therefore, two meta-heuristic algorithms, namely genetic algorithm (GA) and simulated annealing (SA) algorithm, were developed to optimize the integrated scheduling of handling equipment. …”
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    Thesis
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    Optimal location and sizing of battery energy storage system using grasshopper optimization algorithm by Mat Yasin, Zuhaila, Razali, Nur Syifa Nasyrah, Dahlan, Nofri Yenita, Mohammad Noor, Siti Zaliha, Ahmad, Nurfadzilah, Hassan, Elia Erwani

    Published 2024
    “…The grasshopper optimization algorithm (GOA) and evolutionary programming (EP) were employed to address the optimization challenge on the IEEE 69-bus distribution test system. …”
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    Article
  20. 20

    Hybrid conjugate gradient methods using strong Wolfe line search for Whale Optimization Algorithm / Wan Nur Athirah Wan Mohd Zakirudin by Wan Mohd Zakirudin, Wan Nur Athirah

    Published 2023
    “…The nonlinear conjugate gradient (CG) method recently is the most used iterative methods for solving optimizing problems because it requires less storage and easy for implementation. …”
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    Thesis