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  1. 1
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  2. 2
    SEARCH GROUP ALGORITHM FOR MULTI-OBJECTIVE OPTIMIZATION IN ENERGY APPLICATIONS

    SEARCH GROUP ALGORITHM FOR MULTI-OBJECTIVE OPTIMIZATION IN ENERGY APPLICATIONS by TRUONG HOANG, BAO HUY

    Published 2020
    “…This study proposed a new multi-objective version of the Search Group Algorithm (SGA) called the Multi-Objective Search Group Algorithm (MOSGA), aiming for the multi-objective optimization in energy applications. …”
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  3. 3
    Optimization of k-Nearest Neighbour to categorize Indonesian’s news articles

    Optimization of k-Nearest Neighbour to categorize Indonesian’s news articles by Ihsan, Afdhalul, Rainarli, Ednawati

    Published 2021
    “…There are several filter-based feature selection methods; some are Chi-Square, Information Gain, Genetic Algorithm, and Particle Swarm Optimization (PSO). …”
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  4. 4
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  5. 5
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, Hishamuddin, Abd. Samad, M. F., Ahmad, Robiah, Yaacob, M. S.

    Published 2007
    “…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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  6. 6
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, H., Samad, M. F. A., Ahmad, R., Yaacob, M. S.

    Published 2007
    “…he genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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  7. 7
    Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)

    Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD) by Rashed, Alwatben Batoul, Hamdan, Hazlina, Mohd Sharef, Nurfadhlina, Sulaiman, Md Nasir, Yaakob, Razali, Abubakar, Mansir

    Published 2020
    “…However, MOPSO algorithm produces a group of non-dominated solutions which make the selection of an “appropriate” Pareto optimal or non-dominated solution more difficult. …”
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  8. 8
    Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks

    Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks by Han, Fengrong, Izzeldin, Ibrahim Mohamed Abdelaziz, Kamarul Hawari, Ghazali, Zhao, Yue, Li, Ning

    Published 2023
    “…In addition, it also concluded that metaheuristic optimization algorithm and weighted least square method are more suitable to conquer anisotropic factor. …”
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  9. 9
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Abd Samad, Md Fahmi

    Published 2007
    “…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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  10. 10
    Improvement and application of particle swarm optimization algorithm

    Improvement and application of particle swarm optimization algorithm by Deevi, Durga Praveen, Kodadi, Sharadha, Allur, Naga Sushma, Dondapati, Koteswararao, Chetlapalli, Himabindu, Perumal, Thinagaran

    Published 2025
    “…Finally, real-world tests are performed to verify the proposed Algorithm's efficacy compared to existing optimization methods. …”
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  11. 11
    A comprehensive comparison of recent developed meta-heuristic algorithms for streamflow time series forecasting problem

    A comprehensive comparison of recent developed meta-heuristic algorithms for streamflow time series forecasting problem by Ahmed A.N., Van Lam T., Hung N.D., Van Thieu N., Kisi O., El-Shafie A.

    Published 2023
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  12. 12
    Data clustering using the bees algorithm

    Data clustering using the bees algorithm by Pham, D.T, Otri, S., Afify, A., Mahmuddin, Massudi, Al-Jabbouli, H.

    Published 2007
    “…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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  13. 13
    Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri

    Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri by Mohd Sabri, Norlina

    Published 2020
    “…In this research, the empirical experiments have been conducted for the five selected algorithms in the engineering optimization discipline, namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Ant Colony Optimization (ACO) and Artificial Immune System (AIS). …”
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  14. 14
    Clustering ensemble learning method based on incremental genetic algorithms

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

    Published 2012
    “…Two major difficulties in clustering ensemble include diversity of clustering and consensus functions. Genetic algorithms are well known methods with high ability to resolve optimization problems including clustering. …”
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  15. 15
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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  16. 16
    Global optimization method for continuous - Time sensor scheduling

    Global optimization method for continuous - Time sensor scheduling by Woon, Siew Fang, Rehbock, Volker, Loxton, Ryan C.

    Published 2010
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  17. 17
    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed

    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…The application of FES optimized by GA on regionalization creates opportunities for further researches which utilizes different types of optimization like Ant Colony Optimization (ACO), ANN’s, Particle Swarm Optimization (PSO) and Imperialist Competitive Algorithm (ICA).…”
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  18. 18
    Metaheuristic Algorithm for Wellbore Trajectory Optimization

    Metaheuristic Algorithm for Wellbore Trajectory Optimization by Biswas, K., Vasant, P.M., Vintaned, J.A.G., Watada, J.

    Published 2019
    “…Till today so many approaches and methods are used to optimize this wellbore trajectory. …”
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  19. 19
    Asynchronous simulated kalman filter optimization algorithm

    Asynchronous simulated kalman filter optimization algorithm by Zuwairie, Ibrahim, Nor Azlina, Ab. Aziz, Nor Hidayati, Abd Aziz, Tasiransurini, Ab Rahman

    Published 2018
    “…Simulated Kalman filter (SKF) is an optimization algorithm which is inspired by Kalman filtering method. …”
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  20. 20
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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