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  1. 1
    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer

    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

    Published 2021
    “…The mMVO based method is then used for identifying the parameters of linear and nonlinear subsystems in the Hammerstein model using the given input and output data. …”
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  2. 2
    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar

    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

    Published 2019
    “…There is no particular study which focuses on the optimization and prediction of blades parameters using natural inspired algorithms namely Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and Adaptive Neuro-fuzzy Interface System (ANFIS) respectively for optimal power coefficient (�436�45D ). …”
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  3. 3
    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)

    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO) by Ahmed, Ehab Ali

    Published 2019
    “…This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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  4. 4
    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING

    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    Published 2017
    “…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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  5. 5
    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
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  6. 6
    An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system

    An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system by Islam N.N., Hannan M.A., Shareef H., Mohamed A.

    Published 2023
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  7. 7
    Hybrid OCSSA-VMD and optimized deep learning networks for runoff forecasting

    Hybrid OCSSA-VMD and optimized deep learning networks for runoff forecasting by Ma, Hong, Shareduwan Mohd Kasihmuddin, Mohd, Mansor, Mohd. Asyraf, Mohd Jamaludin, Siti Zulaikha, Marsani, Muhammad Fadhil, Che Rose, Farid Zamani

    Published 2025
    “…Prior to feeding the IMFs into the network, the hyperparameters of models were optimized by using the Northern Goshawk Optimization (NGO) algorithm. …”
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  8. 8
    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images

    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

    Published 2024
    “…In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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  9. 9
    Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources

    Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

    Published 2021
    “…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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  10. 10
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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  11. 11
    Multivariate Based Analysis of Methane Adsorption Correlated to Toc and Mineralogy Impact from Different Shale Fabrics

    Multivariate Based Analysis of Methane Adsorption Correlated to Toc and Mineralogy Impact from Different Shale Fabrics by Irfan, S.A., Azli, N.M., Abdulkareem, F.A., Padmanabhan, E.

    Published 2021
    “…The analysis from machine learning SVR method shows the good predictability of the adsorption in the variation with shale fabric parameters. …”
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    Conference or Workshop Item
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  12. 12
    Modeling the Nonlinearity of Sea Level Oscillations in the Malaysian Coastal Areas Using Machine Learning Algorithms

    Modeling the Nonlinearity of Sea Level Oscillations in the Malaysian Coastal Areas Using Machine Learning Algorithms by Lai V., Ahmed A.N., Malek M.A., Afan H.A., Ibrahim R.K., El-Shafie A., El-Shafie A.

    Published 2023
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  13. 13
    Parametric analysis of critical buckling in composite laminate structures under mechanical and thermal loads: a finite element and machine learning approach

    Parametric analysis of critical buckling in composite laminate structures under mechanical and thermal loads: a finite element and machine learning approach by Shabbir Ahmed, Omar, Syed Mohamed Ali, Jaffar, Aabid, Abdul, Hrairi, Meftah, Mohd Yatim, Norfazrina Hayati

    Published 2024
    “…Subsequently, simulation data from numerous cases are utilized to identify the best parameter combination using machine learning algorithms. …”
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  14. 14
    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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  15. 15
    Malware Detection using Deep Learning (DL)

    Malware Detection using Deep Learning (DL) by Chowdhury Sajadul Islam, Madihah Mohd Saudi, Nur Hafiza Zakaria, Muji Setiyo

    Published 2024
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  16. 16
    Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction

    Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction by Jinmei Shi, Yu-Beng Leau, Kun Li, Huandong Chen

    Published 2021
    “…However, most of the existing evolutionary algorithms have some adjustable parameters which depend on subjective experience or prior knowledge. …”
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  17. 17
    The effect of adaptive parameters on the performance of back propagation

    The effect of adaptive parameters on the performance of back propagation by Abdul Hamid, Norhamreeza

    Published 2012
    “…The results show that the proposed algorithm extensively improves the learning process of conventional Back Propagation algorithm.…”
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  18. 18
    Design of intelligent control system and its application on fabricated conveyor belt grain dryer

    Design of intelligent control system and its application on fabricated conveyor belt grain dryer by Lutfy, Omar F.

    Published 2011
    “…Moreover, three evolutionary algorithms (EAs), in particular a real-coded genetic algorithm (GA), a particle swarm optimization (PSO), and a global-best harmony search (GHS), were separately used to train the proposed controller and to determine its scaling factors. …”
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  19. 19
    Application of genetic algorithm methods to optimize flowshop sequencing problem

    Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

    Published 2008
    “…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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    Undergraduates Project Papers
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  20. 20
    Optimisation of fed-batch fermentation process using deep reinforcement learning

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

    Published 2023
    “…Fed-batch fermentation process has always been a challenge for optimisation because it is highly non-linear and complex. Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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