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  1. 1
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  2. 2
    Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences

    Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences by Adnan Ashraf, Sobia Pervaiz, Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Ag. Ibrahim, Joel J. P. C. Rodrigues, Danda B. Rawat

    Published 2021
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  3. 3
    Shooting method with root finding to solve boundary value problems / Aryani Rima Matakim

    Shooting method with root finding to solve boundary value problems / Aryani Rima Matakim by Matakim, Aryani Rima

    Published 2025
    “…In this study, the result of the shooting method combined with various root-finding algorithms such as the Bisection method, Secant method, Newton's method, Ridder's method, Halley’s method, Brent’s method, Modified Newton method and Improved Ostrowski’s method to solve BVPs is evaluated. …”
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  4. 4
    Developing triad design algorithms based on compatible factorization

    Developing triad design algorithms based on compatible factorization by Ibrahim, Haslinda, Omar, Zurni, Abdul Rahim, Rahela

    Published 2011
    “…These processes have helped us develop algorithm for triad design, the objective of this study.A new technique for triad design algorithm, known as Interval Generation Method was employed to construct TD(6n + 1) and TD(6n + 5).This method depends on analyzing the pattern of triples in the design to build starters.We begin by producing starters from Interval Generation Method as the initial block to begin with.Then the algorithm begins by cycling modular v from the initial block and finishes when the process approaches the initial block.The algorithms for TD(6n+1) and TD(6n+5) are presented in Chapter 4 and 5, respectively.As the entire study depends mainly on TD(v) algorithms, new and remarkable theorems and lemmas for TD(v) development are presented and proved.…”
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  5. 5
    Parameter estimation in computational systems biology models: a comparative study of initialization methods in global optimization

    Parameter estimation in computational systems biology models: a comparative study of initialization methods in global optimization by Muhammad Akmal, Remli, Nor Syahidatul Nadiah, Ismail, Noor Azida, Sahabudin, Nor Bakiah, Abd Warif

    Published 2022
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  6. 6
    Clustering ensemble learning method based on incremental genetic algorithms

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…In order to address the above mentioned challenges, this study is devoted towards the development of a clusterer and a clustering ensemble learning method based on incremental genetic algorithms addressing group unlabeled samples. …”
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  7. 7
    Multistage optimal homotopy asymptotic method for solving initial-value problems

    Multistage optimal homotopy asymptotic method for solving initial-value problems by Anakira, N. R., Alomari, A. K., Jameela, Ali, Hashim, Ishak

    Published 2016
    “…In this paper, a new approximate analytical algorithm namely multistage optimal homotopy asymptotic method (MOHAM) is presented for the first time to obtain approximate analytical solutions for linear, nonlinear and system of initial value problems (IVPs).This algorithm depends on the standard optimal homotopy asymptotic method (OHAM), in which it is treated as an algorithm in a sequence of subinterval. …”
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  8. 8
    Parameter estimation of tapioca starch hydrolysis process: Application of least squares and genetic algorithm

    Parameter estimation of tapioca starch hydrolysis process: Application of least squares and genetic algorithm by Roslina, Rashid, Hishamuddin, Jamaluddin, Nor Aishah, Saidina Amin

    Published 2011
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  9. 9
    Parameter estimation of tapioca starch hydrolysis process: application of least squares and genetic algorithm

    Parameter estimation of tapioca starch hydrolysis process: application of least squares and genetic algorithm by Rashid, Roslina, Jamaluddin, Hishamuddin, Saidina Amin, Nor Aishah

    Published 2005
    “…The performance of genetic algorithm (GA) in nonlinear kinetic parameter estimation of topiaca starch hydrolysis was studied and compared with Gauss-Newton method. …”
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  10. 10
    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…In this HPSO algorithm, totally seven particles positions are initialized. …”
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  11. 11
    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 proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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  12. 12
    Novel algorithms of identifying types of Partial Discharges using electrical and non-contact methods / Mohammad Shukri Hapeez

    Novel algorithms of identifying types of Partial Discharges using electrical and non-contact methods / Mohammad Shukri Hapeez by Hapeez, Mohammad Shukri

    Published 2015
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  13. 13
    Comparison between Newton’s Method and a new Scaling Newton Method / Ramizah Baharuddin

    Comparison between Newton’s Method and a new Scaling Newton Method / Ramizah Baharuddin by Baharuddin, Ramizah

    Published 2021
    “…Therefore, in this study, perhaps the researchers will compare the best method between Newton Method and New Scaling Newton Method.…”
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  14. 14
    Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems

    Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems by Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Bin Ag. Ibrahim, Muhammad Reazul Haque, Joel J. P. C. Rodrigues, Danda B. Rawat

    Published 2021
    “…For an optimization problem, population initialization plays a significant role in metaheuristic algorithms. …”
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  15. 15
    Integrated Features by Administering the Support Vector Machine of Translational Initiations Sites in Alternative Polymorphic Context

    Integrated Features by Administering the Support Vector Machine of Translational Initiations Sites in Alternative Polymorphic Context by Nanna Suryana, Herman, Burairah, Hussin

    Published 2012
    “…Many algorithms and methods have been proposed for classification problems in bioinformatics. …”
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  16. 16
    Flexible job shop scheduling using priority heuristics and genetic algorithm

    Flexible job shop scheduling using priority heuristics and genetic algorithm by Farashahi, Hamid Ghaani

    Published 2010
    “…Then, the validation of proposed genetic algorithm with reinforced initial population (GA2) has been checked with random keys genetic algorithm (RKGA). …”
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  17. 17
    Approximating Non Linear Higher Order ODEs By A Three Point Block Algorithm

    Approximating Non Linear Higher Order ODEs By A Three Point Block Algorithm by Nurullah Rasedee, Ahmad Fadly, Abdul Sathar, Mohammad Hasan, Othman, Khairil Iskandar, Hamzah, Siti Raihana, Ishak, Norizarina

    Published 2024
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  18. 18
    Adaptive Initial Contour and Partly-Normalization Algorithm for Iris Segmentation of Blurry Iris Images

    Adaptive Initial Contour and Partly-Normalization Algorithm for Iris Segmentation of Blurry Iris Images by Jamaludin, Shahrizan, Mohamad Ayob, Ahmad Faisal, Mohd Norzeli, Syamimi, Mohamed, Saiful Bahri

    Published 2022
    “…It proved that in blurry iris images, the accurate initial contour position could be established. This algorithm is significant to solve inaccurate segmentation on blurry iris images.…”
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  19. 19
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
    “…The cuckoo search algorithm (CSA) is used in this study for optimizing WNNs. …”
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  20. 20
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
    “…The cuckoo search algorithm (CSA) is used in this study for optimizing WNNs. …”
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