Search Results - (( motion optimization swarm algorithm ) OR ( evolution optimization path algorithm ))

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    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). …”
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    Thesis
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    Performance evaluation of Black Hole Algorithm, Gravitational Search Algorithm and Particle Swarm Optimization by Zuwairie, Ibrahim, Mohamad Nizam, Aliman, Fardila, Naim, Sophan Wahyudi, Nawawi, Shahdan, Sudin

    Published 2015
    “…Particle Swarm Optimization (PSO) and Gravitational Search Algorithm are a well known population-based heuristic optimization techniques. …”
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    Article
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    The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment by Kok, Kai Yit

    Published 2016
    “…Significant research has been conducted on Unmanned Aerial Vehicle (UAV) path planning using evolutionary algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), and Biogeographic-Based Optimization (BBO). …”
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    Thesis
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    A review on particle swarm optimization algorithm and its variants to human motion tracking by Saini, S., Rambli, D.R.B.A., Zakaria, M.N.B., Sulaiman, S.B.

    Published 2014
    “…Several approaches have been proposed in the literature using different techniques.However, conventional approaches such as stochastic particle filtering have shortcomings in computational cost, slowness of convergence, suffers from the curse of dimensionality and demand a high number of evaluations to achieve accurate results. Particle swarm optimization (PSO) is a population-based globalized search algorithm which has been successfully applied to address human motion tracking problem and produced better results in high-dimensional search space.This paper presents a systematic literature survey on the PSO algorithm and its variants to human motion tracking. …”
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    Article
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    Optimization Of Sliding Mode Control Using Particle Swarm Algorithm For An Electro-Hydraulic Actuator System by Rozaimi, Ghazali

    Published 2016
    “…The dynamic parts of electro-hydraulic actuator(EHA) system are widely applied in the industrial field for the process that exposed to the motion control.In order to achieve accurate motion produced by these dynamic parts,an appropriate controller will be needed.However,the EHA system is well known to be nonlinear in nature.A great challenge is carried out in the EHA system modelling and the controller development due to its nonlinear characteristic and system complexity.An appropriate controller with proper controller parameters will be needed in order to maintain or enhance the performance of the utilized controller.This paper presents the optimization on the variables of sliding mode control (SMC) by using Particle Swarm Optimization (PSO) algorithm.The control scheme is established from the derived dynamic equation which stability is proven through Lyapunov theorem.From the obtained simulation results,it can be clearly inferred that the SMC controller variables tuning through PSO algorithm performed better compared with the conventional proportionalintegral-derivative (PID) controller.…”
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    Article
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    Development of an improved GWO algorithm for solving optimal paths in complex vertical farms with multi-robot multi-tasking by Shen, Jiazheng, Hong, Tang Sai, Fan, Luxin, Zhao, Ruixin, Mohd Ariffin, Mohd Khairol Anuar, As’arry, Azizan

    Published 2024
    “…The EPDE-GWO algorithm is compared with Genetic Algorithm (GA), Simulated Annealing (SA), Dung Beetle Optimizer (DBO), and Particle Swarm Optimization (PSO). …”
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    Article
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    A New Approach of Optimal Search Solution in Particle Swarm Optimization (PSO) Algorithm for Object Detection Method by Zalili, Musa, Mohd Hafiz, Mohd Hassin, Nurul Izzatie Husna, Fauzi, Rohani, Abu Bakar, Watada, Junzo

    Published 2018
    “…Therefore, to overcome the several problems associated with the object detection method, a new approach in Particle Swarm Optimization (PSO) algorithm for optimal search solution as an alternative method to detect of object tracking quickly, precisely and accurately. …”
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    Article
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    A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique by Nur Aisyah Syafinaz, Suarin, Pebrianti, Dwi, Bayuaji, Luhur, Muhammad, Syafrullah, Zulkifli, Musa

    Published 2018
    “…This paper aims to adapt Bat Algorithm (BA) optimization techniques to the swarm robotics system. …”
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    Conference or Workshop Item
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    Multi-state PSO GSA for solving discrete combinatorial optimization problems by Ismail, Ibrahim

    Published 2016
    “…Two examples of meta-heuristics are Particle swarm optimization (PSO) and gravitational search algorithm (GSA), which are based on the social behavior of bird flocks and the Newton's law of gravity and the law of motion, respectively. …”
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    Hierarchical approach for articulated 3D human motion tracking using PF-based PSO by Saini, S., Rambli, D.R.B.A., Sulaiman, S.B., Zakaria, M.N.B.

    Published 2014
    “…In this paper, particle filter integrates with particle swarm optimization (PF-PSO) is proposed for articulated 3D human motion tracking. …”
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    Conference or Workshop Item
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    EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization by Too, Jing Wei, Tee, Wei Hown, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

    Published 2019
    “…In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. …”
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    Article
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    Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim by Hashim, Siti Zuraifah

    Published 2007
    “…Roadways and telephone systems are the examples of them. Genetic Algorithms (GA), pioneered by John Holland, applies the principle of evolution found in nature to the problem of finding an optimal solution. …”
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    Thesis
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    Sensitivity analysis on the model input parameters of flapping wing kinematics for optimum level flight via particle swarming optimization by Abdul Hamid, Mohd Faisal

    Published 2018
    “…A systematic iterative process-population-based stochastic algorithm, known as particle swarming optimization, is used. …”
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    Article
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    Accelerated black hole optimization algorithm with enhanced FOPID controller for omni-wheel drive mobile robot system by Basil, Noorulden, Marhoon, Hamzah M., Sahib, Dheyaaldeen Faez, Mohammed, Abdullah Fadhil, Ridha, Hussein Mohammed, Ma’arif, Alfian

    Published 2025
    “…To optimize controller performance, six different optimization algorithms are compared are Accelerated Convergence Black Hole Optimization (ACBHO), Black Hole Optimization (BHO), Aquila Optimizer (AO), Hybrid Firefly Particle Swarm Optimization (HFPSO), Enhanced JAYA (EJAYA), and Sunflower Optimizer (SFO). …”
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    Article
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    Differential evolution optimization for constrained routing in Wireless Mesh Networks by Sanni, Mistura Laide, Hassan Abdalla Hashim, Aisha, Hassan, Wan Haslina, Ahmed, Gharib Subhi Mahmoud, Anwar, Farhat, Zakaria, Omar

    Published 2014
    “…This solution addresses efficient and optimal routing path construction for cost and quality metrics of the application. …”
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    Proceeding Paper
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    Enhancement of ant colony optimization in multi-robot source seeking coordination by Jun Wei Lee, Nyiak Tien Tang, Kit Guan Lim, Min Keng Tan, Baojian Yang

    Published 2019
    “…In hardware platform, the speed of rotation of the wheel is controlled for various movement such as direct motion and rotation in place. Optimization method is focused on ant colony optimization. …”
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    Proceedings
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    Particle swarm optimization with deep learning for human action recognition by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

    Published 2021
    “…The temporal properties of the video sequences undergo computation across full corresponding blocks frames to give motion based information. The features are reduced using the particle swarm optimization detection technique in video image sequences to reduce the computational complexity. …”
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    Article