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  1. 1

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

    Published 2006
    “…Baldwinian learning uses learning algorithm to change the fitness landscape, but the solution that is found is not encoded back into genetic string. …”
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    Article
  2. 2

    Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition by Yew W.H., Fat Chau C., Mahmood Zuhdi A.W., Syakirah Wan Abdullah W., Yew W.K., Amin N.

    Published 2024
    “…These DRL-based algorithms optimize the local and global maximum power point (MPP) using deep Q-learning and deep deterministic policy gradient (DDPG). …”
    Conference Paper
  3. 3

    Particle Swarm Optimization in Machine Learning Prediction of Airbnb Hospitality Price Prediction by Masrom, S., Baharun, N., Razi, N.F.M., Rahman, R.A., Abd Rahman, A.S.

    Published 2022
    “…Particle Swarm Optimization is a meta-heuristics algorithm widely used for optimization problems. …”
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    Article
  4. 4

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

    Published 2019
    “…As network attackers keep changing their methods of attack execution to evade the deployed intrusion-detection systems (IDS), machine learning (ML) algorithms have been introduced to boost the performance of the IDS. …”
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    Conference or Workshop Item
  5. 5

    Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training by Lee, Sen Tan, Zainuddin, Zarita, Ong, Pauline

    Published 2020
    “…Although the gradient information of the commonly used gradient descent training algorithm in WNNs may direct the search to optimal weight solutions that minimize the error function, the learning process is slow due to the complex calculation of the partial derivatives. …”
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  6. 6

    Adaptable algorithms for performance optimization of dynamic batch manufacturing processes by Teo, Kenneth Tze Kin

    Published 2018
    “…The dynamic changes causing the need of dynamic modelling for a better dynamic optimization will be catered via a specifically formulated fitness function. …”
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    Thesis
  7. 7

    New bio-inspired barnacle optimizers based least-square support vector machine for time-series prediction of pandemic outbreaks by Marzia, Ahmed

    Published 2024
    “…The objectives of this research are threefold: firstly, the aim is to create new hybrid optimized machine learning models that improve prediction accuracy; secondly, to overcome limitations in the original Barnacle Mating Optimizer (BMO) and its variants, ensuring the development of robust prediction models; and thirdly, to incorporate vaccination data into the prediction models, enabling adaptation to the dynamic changes in pandemic scenarios. …”
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    Thesis
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    Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee by Chong , Hue Yee

    Published 2023
    “…In this research work, the motivation is to develop an autonomous learning model based on the hybridization of an adaptive ANN and a metaheuristic algorithm for optimizing ANN parameters so that the network could perform learning and adaptation in a more flexible way and handle condition classification tasks more accurately in industries, such as in power systems. …”
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  10. 10

    Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

    Published 2023
    “…This research aimed to determine the optimal feeding strategy for fed-batch baker’s yeast fermentation process using the deep reinforcement learning algorithm in maximising the final production of yeast, while minimising the undesired ethanol formation. …”
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    Forecasting of fine particulate matter based on LSTM and optimization algorithm by Zaini N., Ahmed A.N., Ean L.W., Chow M.F., Malek M.A.

    Published 2024
    “…Long short-term memory based on metaheuristic algorithms, namely particle swarm optimization and sparrow search algorithm (PSO-LSTM and SSA-LSTM), are first developed and applied to determine the significance input combination to the changes of PM2.5 concentration at respective target stations. …”
    Article
  12. 12

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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  13. 13

    Determine the Optimal Diameter of Carbon Steel Pipes Around Undersea Power Cable by Lau, Alvin Kouk Shenn

    Published 2021
    “…Keywords: Undersea Power Cables, cross-linked polyethylene, Eddy Current, Machine Learning Algorithm…”
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    Thesis
  14. 14

    Forecasting FTSE Bursa Malaysia KLCI Trend with Hybrid Particle Swarm Optimization and Support Vector Machine Technique by Lee, Zhong Zhen, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Abraham, Ajith

    Published 2013
    “…This paper hybridizes the Particle Swarm Optimization (PSO) algorithm to generate the optimum features set prior to facilitate SVM learning. …”
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    Conference or Workshop Item
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    Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

    Published 2020
    “…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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    Thesis
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    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. …”
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    Thesis
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    Hybrid ensemble model with optimal weightage for suicidal behavior prediction by Noratikah Nordin, Zurinahni Zainol, Mohd Halim Mohd Noor, Chan, Lai Fong

    Published 2023
    “…Hybridization of soft voting with brute force algorithm has shown that the proposed hybrid ensemble model can find the optimal weights for the machine learning model in the context of predicting suicidal behavior. …”
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    Article
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