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  1. 1
    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms

    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

    Published 2017
    “…Meanwhile, the proposed QOJaya algorithm produces better results than the basic Jaya method in terms of solution optimality and convergence speed. …”
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  2. 2
    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System

    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

    Published 2019
    “…In this paper, the particle swan optimization algorithm (PSO) was used to obtain an optimal set of initial parameters for Reduce Kernel FLN (RK-FLN), thus, creating an optimal RKFLN classifier named PSO-RKELM. …”
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  3. 3
    Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim

    Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim by Kamarzaman, Nur Atharah, Sulaiman, Shahril Irwan, Ibrahim, Intan Rahayu

    Published 2021
    “…Numerical results indicate that the ASSO algorithm strategy outperforms the basic SSO algorithm, Genertic Algorithm (GA), Particle Swarm Intelligence (PSO), Firefly Algorithm (FA), Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TBLO) in term of reaching for global solution.…”
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  4. 4
    Nomadic people optimizer (NPO) for large-scale optimization problems

    Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

    Published 2019
    “…Researchers have in the past few decades resorted to several methods that are inspired from complex optimization problems. …”
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  5. 5
    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach

    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

    Published 2022
    “…The other one is the network training’s environment optimization that is done through hyperparameter optimization by selecting and fine-tuning high impact parameters which include Optimizer, Learning Rate and Dropout to reduce error rate (loss function). …”
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  6. 6
    Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection

    Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection by Ghanem, Waheed Ali Hussein Mohammed

    Published 2019
    “…Those problems lend themselves to the realm of optimization. Considering the wide success of swarm intelligence methods in optimization problems, the main objective of this thesis is to contribute to the improvement of intrusion detection technology through the application of swarm-based optimization techniques to the basic problems of selecting optimal packet features, and optimal training of neural networks on classifying those features into normal and attack instances. …”
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  7. 7
    Mean of correlation method for optimization of affective states detection in children

    Mean of correlation method for optimization of affective states detection in children by Rusli, Nazreen, Sidek, Shahrul Na'im, Md Yusuf, Hazlina, Ishak, Nor Izzati

    Published 2018
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  8. 8
    A simplified PID-like ANFIS controller trained by genetic algorithm to control nonlinear systems

    A simplified PID-like ANFIS controller trained by genetic algorithm to control nonlinear systems by Lutfy, Omar Farouq, Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce, Abbas, Kassim A.

    Published 2010
    “…Moreover, the GA was used to find the optimal settings for the input and output scaling factors for this controller, instead of the widely used trial and error method. …”
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  9. 9
    Improving neural networks training using experiment design approach

    Improving neural networks training using experiment design approach by Chong, Wei Kean

    Published 2005
    “…This data is selected by two methods: random and Experiment Design Approach (D-optimal and Maxmin Distance). …”
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  10. 10
    Image Splicing Detection With Constrained Convolutional Neural Network

    Image Splicing Detection With Constrained Convolutional Neural Network by Lee, Yang Yang

    Published 2019
    “…It is shown that CNN with constrained convolution algorithm can be used as a general image splicing detection task.…”
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  11. 11
    Designing an integrated AIOT system for tracking class attendance

    Designing an integrated AIOT system for tracking class attendance by Kuak, Xuan Ren

    Published 2024
    “…Basics and ensures that the software is more secure than the previous traditional attendance method using roll-less slides. …”
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  12. 12
    CFD modeling on coal properties towards the burnout efficiency

    CFD modeling on coal properties towards the burnout efficiency by Nabil Asyraf Abd Halim

    Published 2024
    text::Final Year Project
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  13. 13
    Review and bibliometric analysis of AI-driven advancements in healthcare

    Review and bibliometric analysis of AI-driven advancements in healthcare by Wang, Yi Jie, Choo, Wei Chong, Ng, Keng Yap

    Published 2024
    “…Research shows that "algorithm", "machine learning", "deep learning", "controlled study", "major clinical study" and "healthcare delivery" as well as "decision support systems" are key topics for research. …”
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  14. 14
    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems

    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

    Published 2022
    “…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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  15. 15
    Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour

    Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour by Neyamadpour, Ahmad

    Published 2010
    “…These methods are M1 and M2, and they basically differ in the type of input-output data used to train the artificial neural network. …”
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  16. 16
    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network

    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
    “…Hybrid genetic algorithms are the combination of learning algorithms(Back propagation), usually working as evaluation functions, and genetic algorithms. …”
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  17. 17
    A hybrid particle swarm optimization - extreme learning machine approach for intrusion detection system

    A hybrid particle swarm optimization - extreme learning machine approach for intrusion detection system by M.H., Ali, Mohamad, Fadlizolkipi, Ahmad Firdaus, Zainal Abidin, Nik Zulkarnaen, Khidzir

    Published 2018
    “…This work proposes the extreme learning machine (ELM) is one of the poplar machine learning algorithms which, easy to implement with excellent learning performance characteristics. …”
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  18. 18
    Predictive modeling and feature attribution of CO₂ adsorption on LDH-derived materials using machine learning approach

    Predictive modeling and feature attribution of CO₂ adsorption on LDH-derived materials using machine learning approach by Pinto, Mavin Jason, Sharath, S. S., Sudhakar, K., Priya, S. Shanmuga, Thirunavukkarasu, I.

    Published 2025
    “…Moderate calcination of the material emerges as the optimal synthesis window, which results in balanced porosity, structural stability, and basic site density. …”
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  19. 19
    Automated bilateral negotiation with incomplete information in the e-marketplace.

    Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

    Published 2011
    “…The reason is that, SRT algorithm is sensitive to the accuracy of the learned preferences while MGT algorithm can generate Pareto-optimal offers even with an approximation of the learned preferences.…”
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  20. 20
    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution

    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

    Published 2018
    “…An intelligence strategy called quasi-oppositional based learning is incorporated into the proposed algorithm to enhance its convergence property, exploration capability, and solution optimality. …”
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