Search Results - (( evolution optimization method algorithm ) OR ( pattern optimization swarm algorithm ))

Refine Results
  1. 1

    A novel Master–Slave optimization algorithm for generating an optimal release policy in case of reservoir operation by Turgut, Mert Sinan, Turgut, Oguz Emrah, Afan, Haitham Abdulmohsin, El-Shafie, Ahmed

    Published 2019
    “…First, three different optimization algorithms, namely particle swarm optimization, differential evolution, and whale optimization algorithm, have been applied. …”
    Get full text
    Get full text
    Article
  2. 2

    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…The third method is the hybridization of BPSO and Binary Differential Evolution, namely Binary Particle Swarm Optimization Differential Evolution (BPSODE). …”
    Get full text
    Get full text
    Get full text
    Thesis
  3. 3

    Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2025
    “…The study compares the proposed CNN-LSTM-BMO against other metaheuristic optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Differential Evolution (DE). …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4

    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 study, a pattern based using Particle Swarm Optimization (PSO) is proposed named as Hexagon PSO (HPSO). …”
    Get full text
    Get full text
    Thesis
  5. 5

    A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application by Zainal Abidin, Zulkifli

    Published 2011
    “…The objective of the simulation is to understand the effect of the algorithm parameter on searching pattern strategy, as well as the possibility and the effectiveness of the proposed technique for the Swarm of mini Autonomous Surface Vehicles' (ASVs) application.…”
    Get full text
    Get full text
    Get full text
    Article
  6. 6

    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). …”
    Get full text
    Get full text
    Get full text
    Article
  7. 7
  8. 8

    Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari by Mohammed , Heydari

    Published 2017
    “…An improved particle swarm algorithm (HPSOGA) is used to solve complex problems of water resources optimization. …”
    Get full text
    Get full text
    Get full text
    Thesis
  9. 9

    An Adaptive Switching Cooperative Source Searching And Tracing Algorithms For Underwater Acoustic Source Localization by Majid, Mad Helmi Ab.

    Published 2019
    “…Secondly, to trace the source to its approximate location, a Source Tracing Algorithm (STA) known as an Asynchronous Dynamically Adjustable Particle Swarm Optimization (ADAPSO) is suggested. …”
    Get full text
    Get full text
    Thesis
  10. 10

    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.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  11. 11
  12. 12

    Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification by Nuaimi, Zakaria Noor Aldeen Mahmood Al, Abdullah, Rosni

    Published 2017
    “…Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
    Get full text
    Get full text
    Get full text
    Article
  13. 13
  14. 14

    Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification by Al Nuaimi, Zakaria Noor Aldeen Mahmood, Abdullah, Rosni

    Published 2017
    “…By optimizing the training of the neural networks using optimal weight set, better results can be obtained by the neural networks.Traditional neural networks algorithms such as Back Propagation (BP) were used for ANNT, but they have some drawbacks such as computational complexity and getting trapped in the local minima.Therefore, evolutionary algorithms like the Swarm Intelligence (SI) algorithms have been employed in ANNT to overcome such issues.Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
    Get full text
    Get full text
    Get full text
    Article
  15. 15
  16. 16

    Hybrid particle swarm optimization for robust digital image watermarking by Tao, Hai, Jasni, Mohamad Zain, Abdalla, Ahmed N., Mohammad Masroor, Ahmed

    Published 2011
    “…The novelty is to associate the Hybrid Particle Swarm Optimization (HPSO), instead of a single optimization, as a model with singular value decomposition (SVD). …”
    Get full text
    Get full text
    Get full text
    Article
  17. 17

    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
    “…Besides, weighted least square method is adopted to replace the least square method to against anisotropic factors caused by irregular radio patterns. Moreover, an Autonomous Groups Particles Swarm Optimization (AGPSO) is employed to further optimize the obtained coordinate in the first round. …”
    Get full text
    Get full text
    Get full text
    Article
  18. 18

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…The proposed method is tested on 10 multi-objective benchmark problems of CEC 2009 and compared with four metaheuristics: Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), Multi-Objective Differential Evolution (MODE) and MOPSO. …”
    Get full text
    Get full text
    Thesis
  19. 19

    A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom, Sampe, Jahariah

    Published 2022
    “…In accordance with the result, this article proposes a novel chew count estimation based on particle swarm optimization (PSO). First, the base of the algorithm is developed based on counting the peak of the chewing signal. …”
    Get full text
    Get full text
    Article
  20. 20

    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
    Get full text
    Get full text
    Get full text
    Article