Search Results - (( parameter optimization sensor algorithm ) OR ( swarm optimization max algorithm ))

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  1. 1

    A particle swarm optimization and min-max­-based workflow scheduling algorithm with QoS satisfaction for service-­oriented grids by Ambursa, Faruku Umar, Latip, Rohaya, Abdullah, Azizol, K. Subramaniam, Shamala

    Published 2017
    “…It also outperforms the comparison algorithm, with about 30% increase, in terms of cumulative QoS satisfaction of optimization requirements. …”
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    Article
  2. 2

    Performance comparison of differential evolution and particle swarm optimization in constrained optimization by Iwan, Mahmud, Akmeliawati, Rini, Faisal, Tarig, Al-Assadi, Hayder M.A.A.

    Published 2012
    “…Particle swarm optimization (PSO) and differential evolution (DE) are among the well-known modern optimization algorithms. …”
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  3. 3

    Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

    Published 2014
    “…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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  4. 4

    Artificial neural network-salp-swarm algorithm for stock price prediction by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Azlan, Abdul Aziz

    Published 2024
    “…Additionally, the SSA-ANN model is compared with other two hybrid models: the ANN optimized by the Whale Optimization Algorithm (WOA-ANN) and Moth-Flame Optimizer (MOA-ANN), as well as a single model, namely the Autoregressive Integrated Moving Average (ARIMA). …”
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  5. 5

    A quantum-inspired particle swarm optimization approach for environmental/economic power dispatch problem using cubic criterion function by Mahdi, F.P., Vasant, P., Abdullah-Al-Wadud, M., Watada, J., Kallimani, V.

    Published 2018
    “…Many-objective EED problems are defined by using a cubic criterion function, and a max/max price penalty factor is considered to convert all the objectives into a single objective to compare the final results with other well-known methods found in the literature like Lagrangian relaxation, particle swarm optimization, simulated annealing, and quantum-behaved bat algorithm. …”
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  6. 6

    A quantum-inspired particle swarm optimization approach for environmental/economic power dispatch problem using cubic criterion function by Mahdi, F.P., Vasant, P., Abdullah-Al-Wadud, M., Watada, J., Kallimani, V.

    Published 2018
    “…Many-objective EED problems are defined by using a cubic criterion function, and a max/max price penalty factor is considered to convert all the objectives into a single objective to compare the final results with other well-known methods found in the literature like Lagrangian relaxation, particle swarm optimization, simulated annealing, and quantum-behaved bat algorithm. …”
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  7. 7

    Interacted Multiple Ant Colonies for Search Stagnation Problem by Aljanabi, Alaa Ismael

    Published 2010
    “…Ant Colony Optimization (ACO) is a successful application of swarm intelligence. …”
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    Thesis
  8. 8

    Reactive memory model for ant colony optimization and its application to TSP by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2014
    “…Ant colony optimization is one of the most successful examples of swarm intelligent systems. …”
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  9. 9

    Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Ahmad Salihin, Samsudin, Amir Izzani, Mohamed, Mohd Mawardi, Saari

    Published 2025
    “…A comprehensive data preprocessing pipeline was implemented, including missing value treatment, outlier removal, and feature normalization using Min-Max scaling. Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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  10. 10

    Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: a review paper by Qadori, Huthiafa Q., Ahmad Zukarnain, Zuriati, Mohd Hanapi, Zurina, Subramaniam, Shamala

    Published 2017
    “…The review shows that most of the algorithms used one parameter to find the optimal number of mobile agents in multi-agent itinerary planning without utilizing other parameters. …”
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  11. 11

    Performance comparison of GA and PSO based ANN training on medical dataset / Muhammad Amirul Danish Jamal by Jamal, Muhammad Amirul Danish

    Published 2025
    “…This research performs a comparative analysis of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) as methods for optimizing the training of ANNs, utilizing three medical datasets: Breast Cancer Wisconsin, Cleveland Heart Disease, and Pima Indian Diabetes. …”
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    Thesis
  12. 12

    Parameter adaptation for ant colony system in wireless sensor network by Abdul Nasir, Husna Jamal, Ku-Mahamud, Ku Ruhana, Kamioka, Eiji

    Published 2019
    “…The Ant Colony System (ACS) algorithm has been applied in solving packet routing problems in Wireless Sensor Networks (WSNs). …”
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  13. 13

    Social spider optimisation algorithm for dimension reduction of electroencephalogram signals in human emotion recognition by Al-Qammaz, Abdullah Yousef, Ahmad, Farzana Kabir, Yusof, Yuhanis

    Published 2018
    “…Due to some limitations of current heuristics and evolutionary algorithms, this paper proposed a new swarm based algorithm for feature selection method called Social Spider Optimization (SSO-FS). …”
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  14. 14

    Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

    Published 2025
    “…One of the powerful optimization algorithms that is used for feature selection is the Whale Optimization Algorithm (WOA), which is a nature-inspired metaheuristic optimization algorithm that mimics the social behavior of humpback whales. …”
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  15. 15

    Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali by Ihsan , Ali

    Published 2024
    “…The IDBA-AFW evaluates the fitness of relay nodes based on multiple criteria, such as energy efficiency, throughput, and end-to-end delay. Both Bat Algorithm parameters and AFW parameters are adaptively tuned to balance exploration and exploitation throughout the optimization process. …”
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    Thesis
  16. 16

    Optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm by Farah Nur Arina, Baharudin, Nor Azlina, Ab. Aziz, Mohamad Razwan, Abdul Malek, Zuwairie, Ibrahim

    Published 2021
    “…In this work, these parameters are optimized using dynamic inertia weight artificial bees colony (DIW-ABC) optimization algorithm. …”
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  17. 17

    A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network by Almuslehi, Hussein Saad Mohammed

    Published 2023
    “…Compared to the Ant Colony Optimization-Genetic Algorithm (ACO-GA) and Ant Colony Optimization- Hierarchical Clustering Mechanism (ACOHCM), the ACO algorithm shows superior power savings and efficiency. …”
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    Thesis
  18. 18

    DC Motor Control using Ant Colony Optimization by Amr Mansour, Sara

    Published 2011
    “…Since 1995 various other extended versions of AS have been developed, induding Ant Colony System (ACS) and MAX-MIN Ant System (MMAS). In 1999 Dorigo proposed the Ant Colony Optimization (ACO) meta-heuristic that became the most successful and recognized algorithm based on ant behaviour [1]. …”
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    Final Year Project
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