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  1. 1
    Optimized clustering with modified K-means algorithm

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
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  2. 2
    Fuzzy clustering method and evaluation based on multi criteria decision making technique

    Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

    Published 2018
    “…The new proposed method (MBPSO+MKN+GK) Gustafson- Kessel algorithm (GK)integrated with modified of Kohonen Network algorithm (MKN)and modified binary particle swarm optimization (MBPSO) was used to classify the credit scoring data. …”
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  3. 3
    System identification using Extended Kalman Filter

    System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

    Published 2017
    “…Besides, Extended Kalman Filter (EKF) algorithm was selected in this project as an algorithm for offline estimation data purposes. …”
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  4. 4
    Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems

    Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

    Published 2024
    “…The main motivations for investigating IWD algorithm are: (i) IWD has been successfully employed to solve many optimization problems. …”
    thesis::doctoral thesis
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  5. 5
    A dynamic replication aware load balanced scheduling for data grids in distributed environments of internet of things

    A dynamic replication aware load balanced scheduling for data grids in distributed environments of internet of things by Bakhshad, Said, Noor, Rafidah Md, Akhundzada, Adnan, Saba, Tanzila, Ahmedy, Ismail, Haroon, Faisal, Nazir, Babar

    Published 2018
    “…The simulation of the proposed algorithm shows promising results and better performance compared to the current state-of-the-art Modified Dynamic Hierarchical Replication (MDHR) algorithm. …”
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  6. 6
    Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia

    Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

    Published 2019
    “…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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  7. 7
    A Subspace Approach for Extracting Signals Highly Corrupted by Colored Noise

    A Subspace Approach for Extracting Signals Highly Corrupted by Colored Noise by Yusoff, Mohd Zuki, Hussin, Fawnizu Azmadi

    Published 2010
    “…SNR values can be as low as -10 dB in real clinical environments. The simulation results produced by the post-modified SSA2 algorithm, show a higher degree of consistencies in detecting the VEP's P100, P200, and P300 peaks, in comparisons to the pre-modified SSA1 method. …”
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    Citation Index Journal
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  8. 8
    Performance of amidoxime-modified poly(acrylonitrile- Co-acrylic acid) for removal of boron in aqueous solution

    Performance of amidoxime-modified poly(acrylonitrile- Co-acrylic acid) for removal of boron in aqueous solution by Lau, Kia Li

    Published 2019
    “…Meanwhile, the Artificial Neural Network (ANN) was simulated from experimental data and applied to optimize, develop and create prediction models for boron adsorption by AO-modified poly(AN-co-AA). …”
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  9. 9
    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation

    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

    Published 2019
    “…Furthermore, to evaluate the efficiency of the proposed modified differential evolution for the training of ridgelet probabilistic neural network, four statistical search techniques, namely, particle swarm optimization, genetic algorithm, simulated angling, and classical differential evolution are used and their results are compared. …”
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  10. 10
    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems

    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

    Published 2024
    “…In the fourth phase, the newly developed algorithm undergoes testing on the formulated ROOPs and compared to several contemporary optimizer algorithms. …”
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  11. 11
    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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  12. 12
    Impact of evolutionary algorithm on optimization of nonconventional machining process parameters

    Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

    Published 2025
    “…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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  13. 13
    Determining optimal location of static VAR compensator by means of genetic algorithm

    Determining optimal location of static VAR compensator by means of genetic algorithm by Karami, Mahdi, Mariun, Norman, Ab Kadir, Mohd Zainal Abidin

    Published 2011
    “…This method is employed to optimize the stability of power system by means of maximizing distance to collapse point. …”
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  14. 14
    An ensemble of neural network and modified grey wolf optimizer for stock prediction

    An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

    Published 2019
    “…Additionally, the research restricts the number of variables through feature selection to enhance the performance of the algorithm. Subsequently, the research attempts to construct an ensemble model applying Modified Grey Wolf Optimizer (MGWO) and neural network for stock prediction. …”
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  15. 15
    Studying the Effect of Training Levenberg Marquardt Neural Network by Using Hybrid Meta-Heuristic Algorithms

    Studying the Effect of Training Levenberg Marquardt Neural Network by Using Hybrid Meta-Heuristic Algorithms by Abubakar, A., Khan, A., Nawi, N.M., Rehman, M.Z., Teh, Y.W., Chiroma, H., Herawan, T.

    Published 2016
    “…The simulation results show that the APSO-LM algorithm shows better performance than baseline algorithms in terms of convergence speed and Mean Squared Error (MSE).…”
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  16. 16
    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network

    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

    Published 2016
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  17. 17
    Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links

    Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links by Arif, M., Khan, S.S., Qadri, S.S.U., Naseem, I., Moinuddin, M.

    Published 2022
    “…The analytical results are validated through simulation. Finally, extensive simulations have been done to evaluate the performance of the proposed algorithm for various choices of optimal q-values. …”
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  18. 18
    Optimalisation of a job scheduler in the grid environment by using fuzzy C-mean

    Optimalisation of a job scheduler in the grid environment by using fuzzy C-mean by Lorpunmanee, Siriluck, Abdullah, Abdul Razak

    Published 2007
    “…Simulation runs demonstrate that our algorithm leads to better results than the traditional algorithms for scheduling policies used in Grid environment.…”
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  19. 19
    Modified K-Nearest Neighborhood Algorithm For Optimal Selection Of Distribution Centre In The Disaster Relief Operation

    Modified K-Nearest Neighborhood Algorithm For Optimal Selection Of Distribution Centre In The Disaster Relief Operation by Siti Nabilah Basarang

    Published 2024
    thesis::master thesis
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  20. 20
    Studying the effect of training Levenberg Marquardt neural network by using hybrid meta-heuristic algorithms

    Studying the effect of training Levenberg Marquardt neural network by using hybrid meta-heuristic algorithms by Abubakar, Adamu, Khan, Abdullah, Nawi, Nazri Mohd, Rehman, M. Z., Teh , Ying Wah, Chiroma , Haruna, Herawan, Tutut

    Published 2016
    “…The simulation results show that the APSO-LM algorithm shows better performance than baseline algorithms in terms of convergence speed and Mean Squared Error (MSE).…”
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