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  1. 1
    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
    “…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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  2. 2
    Optimizing n-1 contingency rankings using a nature-inspired modified sine cosine algorithm

    Optimizing n-1 contingency rankings using a nature-inspired modified sine cosine algorithm by Priyadi, Irnanda, Daratha, Novalio, Gunawan, Teddy Surya, Ramli, Kalamullah, Jalistio, Febrian, Mokhlis, Hazlie

    Published 2025
    “…% of the search space, and requires a processing time of 3.69 seconds. Compared with established methods such as Ant Colony Optimization (ACO) and Genetic Algorithm (GA), MSCA exhibits superior computational efficiency while maintaining competitive accuracy. …”
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  3. 3
    Improved cuckoo search based neural network learning algorithms for data classification

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…This research proposed an improved CS called hybrid Accelerated Cuckoo Particle Swarm Optimization algorithm (HACPSO) with Accelerated particle Swarm Optimization (APSO) algorithm. …”
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  4. 4
    Graph theory approach for managing lecturers’ schedule using graph colouring method / Siti Nor Ba Basri, Nur Su’aidah Khozaid and Farhana Hazwani Ismail

    Graph theory approach for managing lecturers’ schedule using graph colouring method / Siti Nor Ba Basri, Nur Su’aidah Khozaid and Farhana Hazwani Ismail by Basri, Siti Nor Ba, Khozaid, Nur Su’aidah, Ismail, Farhana Hazwani

    Published 2023
    “…Different colours are allocated to each vertex using graph colouring techniques such as the vertices algorithm or the edges algorithm, ensuring that clashing courses and lecturers are assigned different time slots. …”
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  5. 5
    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah by Salmah , Fattah

    Published 2022
    “…Finally, the proposed algorithm’s effectiveness regarding node coverage, energy consumption, Pareto-optimal value, and algorithm execution time is validated using three Pareto-optimal metrics: including inverted generation distance (IGD), hypervolume, and diversity. …”
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  6. 6
    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks by Salmah Fattah

    Published 2022
    “…Finally, the proposed algorithm's effectiveness regarding node coverage, energy consumption, Pareto-optimal value, and algorithm execution time is validated using three Pareto-optimal metrics: including inverted generation distance (IGD), hypervolume, and diversity. …”
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  7. 7
    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio

    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio by Wang, B., Li, Y., Wang, S., Watada, J.

    Published 2018
    “…Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
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  8. 8
    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio

    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio by Wang, B., Li, Y., Wang, S., Watada, J.

    Published 2018
    “…Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
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  9. 9
    Route optimization security in mobile IPv6 wireless networks: a test-bed experience

    Route optimization security in mobile IPv6 wireless networks: a test-bed experience by Mehdizadeh, Abbas, Khatun, Sabira, Mohd Ali, Borhanuddin, Raja Abdullah, Raja Syamsul Azmir, Kurup, Gopakumar

    Published 2008
    “…The real-time network Test-bed is implemented to prove the efficiency of proposed method. …”
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  10. 10
    Improving earth surface temperature forecasting through the optimization of deep learning hyper-parameters using barnacles mating optimizer

    Improving earth surface temperature forecasting through the optimization of deep learning hyper-parameters using barnacles mating optimizer by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Muhammad 'Arif, Mohamad

    Published 2024
    “…To improve the DL model's performance, an optimization algorithm called Barnacles Mating Optimizer (BMO) is integrated to optimize both weights and biases. …”
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  11. 11
    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
    “…In particular, this study proposes a crime prediction and evaluation framework for machine learning algorithms of the network edge. …”
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  12. 12
    Security enhancement of route optimization in mobile IPv6 networks

    Security enhancement of route optimization in mobile IPv6 networks by Mehdizadeh, Abbas, Khatun, Sabira, Mohd Ali, Borhanuddin, Raja Abdullah, Raja Syamsul Azmir, Kurup, Gopakumar

    Published 2008
    “…The real-time network Test-bed is implemented to prove the efficiency of proposed method. …”
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  13. 13
    Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods

    Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods by Kadhem, Athraa Ali

    Published 2017
    “…The reliability assessment of the adequacy of the generating system is normally calculated by using either analytical or simulation methods. The Monte Carlo simulation (MCS) method enables an accurate evaluation of reliability indices. …”
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  14. 14
    Optimized techniques for landslide detection and characteristics using LiDAR data

    Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

    Published 2018
    “…Also, six techniques: Ant Colony Optimization (ACO), Gain Ratio (GR), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), Random forest (RF), and Correlation-based Feature Selection (CFS) were used for the feature selection. …”
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  15. 15
    Detection of black hole attacks in mobile ad hoc networks via HSA-CBDS method

    Detection of black hole attacks in mobile ad hoc networks via HSA-CBDS method by Fahad, Ahmed Mohammed, Ahmed, Abdulghani Ali, Alghushami, Abdullah H., Alani, Sammer

    Published 2019
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  16. 16
    Radiomics analysis and supervised machine learning model for classification of cervical cancer images using diffusion weighted imaging-MRI

    Radiomics analysis and supervised machine learning model for classification of cervical cancer images using diffusion weighted imaging-MRI by Ramli, Zarina

    Published 2024
    “…Additionally, the SVM algorithm was evaluated based on its performance across different DWI bvalues, aiming to optimize scanning time. …”
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  17. 17
    A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal

    A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal by Aymen Taher , Ahmed al-Ashwal

    Published 2019
    “…By evaluating the model on food dataset FOOD101, extracting of features take 80.23 seconds and classifying and training of incremental algorithm take 1253.36 seconds with 77.72% test accuracy. …”
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  18. 18
    Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost

    Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost by Chen, Suihai, Bong, Chih How, Chiu, Po Chan

    Published 2024
    “…PSO-EBGWO is used to optimize the parameters of the CatBoost model. In this method, the Gray Wolf optimized algorithm (EBGWO) is further optimized by particle swarm optimization (PSO), and when combined with it, the convergence performance of the model is improved, the parameters of the model are reduced, and the model is simplified. …”
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  19. 19
    Multi-Objective Portfolio Optimization Strategy using the SPEA-II Algorithm

    Multi-Objective Portfolio Optimization Strategy using the SPEA-II Algorithm by Azarberahman, Alireza, Tohidinia, Malihe, Aliakbarzadeh, Hossein

    Published 2025
    “…The study highlights that the SPEA-II algorithm can serve as an effective and efficient method for stock portfolio selection and optimization, helping investors to identify portfolios with lower risk and higher return…”
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  20. 20
    An Empirical Study on the Construction of A Non-Convex Risk Parity Portfolio using a Genetic Algorithm

    An Empirical Study on the Construction of A Non-Convex Risk Parity Portfolio using a Genetic Algorithm by Kusumawati, Rosita, Rosadi, Dedi, Abdurakhman, Abdurakhman

    Published 2025
    “…While conventional numerical methods can be applied, they often struggle with inefficiency and fail to deliver optimal results. …”
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