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  1. 1
    Develpoment of combinatorial optimisation for cutting tool path strategy

    Develpoment of combinatorial optimisation for cutting tool path strategy by Alsultaney, Hazem K., Mohd Ariffin, Mohd Khairol Anuar, Baharudin, B. T. Hang Tuah, Ali, Aidy, Mustapha, Faizal

    Published 2009
    “…This work aims to optimise the tool path by simulating the removal of material in a finite element environment, which is controlled by a Genetic Algorithm. …”
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  2. 2
    An experimental validation and optimisation tool path strategy for thin walled structure

    An experimental validation and optimisation tool path strategy for thin walled structure by Alsultaney, Hazem K., Mohd Ariffin, Mohd Khairol Anuar, Baharudin, B. T. Hang Tuah, Ali, Aidy, Mustapha, Faizal

    Published 2011
    “…This work was carried out with the aim to optimise the tool path by simulating the removal of material in a finite element environment which is controlled by a genetic algorithm (GA). …”
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  3. 3
    Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation

    Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation by Toha, Siti Fauziah, Abd Latiff, I., Mohamad, M., Tokhi, M Osman

    Published 2009
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  4. 4
    A hybrid residue based sequential encoding mechanism with XGBoost improved ensemble model for identifying 5-hydroxymethylcytosine modifications

    A hybrid residue based sequential encoding mechanism with XGBoost improved ensemble model for identifying 5-hydroxymethylcytosine modifications by Uddin I., Awan H.H., Khalid M., Khan S., Akbar S., Sarker M.R., Abdolrasol M.G.M., Alghamdi T.A.H.

    Published 2025
    “…Among the applied machine learning algorithms, the XGBoost ensemble model using the tenfold cross-validation test achieved improved results than existing state-of-the-art models. …”
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  5. 5
    Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems

    Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems by Abdul Hamid, Norhamreeza, Mohd Nawi, Nazri, Ghazali, Rozaida, Mohd Salleh, Mohd Najib

    Published 2011
    “…Over the years, many improvements and modifications of the back propagation learning algorithm have been reported. …”
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  6. 6
    Unit commitment in power system using multi-agent evolutionary programming incorporating priority listing optimisation technique / Muhammad Nazree Che Othman

    Unit commitment in power system using multi-agent evolutionary programming incorporating priority listing optimisation technique / Muhammad Nazree Che Othman by Che Othman, Muhammad Nazree

    Published 2013
    “…The developed technique was tested on the 10 generating units test system then up to 20 generating units in a 24-hours scheduling period and the results was compared with the basic EP, Evolutionary Programming with Priority Listing (EP-PL) and Multi-agent Evolutionary Programming (MAEP) optimisation techniques. …”
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  7. 7
    Different mutation and crossover set of genetic programming in an automated machine learning

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…Automated machine learning is a promising approach widely used to solve classification and prediction problems, which currently receives much attention for modification and improvement. …”
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  8. 8
    Different mutation and crossover set of genetic programming in an automated machine learning

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…Automated machine learning is a promising approach widely used to solve classification and prediction problems, which currently receives much attention for modification and improvement. …”
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  9. 9
    Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms

    Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

    Published 2008
    “…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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  10. 10
    Learning to filter text in forum message

    Learning to filter text in forum message by Sainin, Mohd Shamrie

    Published 2005
    “…In this paper, the modification of the algorithm including pre-processing and classification will be discussed in the attempt to apply learning to filter forum messages.…”
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  11. 11
    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
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  12. 12
    Three-term backpropagation algorithm for classification problem

    Three-term backpropagation algorithm for classification problem by Saman, Fadhlina Izzah

    Published 2006
    “…Standard Backpropagation Algorithm (BP) is a widely used algorithm in training Neural Network that is proven to be very successful in many diverse application. …”
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  13. 13
    A new variant of black hole algorithm based on multi population and levy flight for clustering problem

    A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

    Published 2020
    “…Furthermore, the results revealed a high convergence rate, upon which the algorithm’s performance was subjected to data clustering problems and investigated using six real datasets. …”
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  14. 14
    Edge assisted crime prediction and evaluation framework for machine learning algorithms

    Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

    Published 2022
    “…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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  15. 15
    An approach to improve functional link neural network training using modified artificial bee colony for classification task

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Yana Mazwin Mohmad Hassim, Rozaida Ghazali

    Published 2013
    “…To overcome this, a Functional Link Neural Networks (FLNN), which has single layer of trainable connection weight is used. The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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  16. 16
    An approach to improve functional link neural network training using modified artificial bee colony for classification task

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2012
    “…To overcome this, a Functional Link Neural Networks (FLNN), which has single layer of trainable connection weight is used. The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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  17. 17
    An approach to improve functional link neural network training using modified artificial bee colony for classification task

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2012
    “…To overcome this, a Functional Link Neural Networks (FLNN), which has single layer of trainable connection weight is used. The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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  18. 18
    Grammar-based prosody modification for explicit control Malay language storytelling speech synthesis / Muhammad Izzad Ramli

    Grammar-based prosody modification for explicit control Malay language storytelling speech synthesis / Muhammad Izzad Ramli by Ramli, Muhammad Izzad

    Published 2018
    “…Using Harmonic Noise Model (HNM) as the synthesizer, the grammar-based prosody modification rules are used to produce the synthesized storytelling speech. …”
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  19. 19
    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
    “…By considering these limitations, two modifications were made upon the conventional MVO in our proposed mMVO algorithm. …”
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  20. 20
    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques

    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

    Published 2011
    “…Unfortunately, the traditional mechanisms designed for protecting networks are not directly applicable to MANETs without modifications. In the past decades, machine learning methods have been successfully used in several intrusion detection methods because of their ability to discover and detect novel attacks. …”
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