Search Results - (( using optimization method algorithm ) OR ( abc implementation based algorithm ))
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1
Global gbest guided-artificial bee colony algorithm for numerical function optimization
Published 2018“…Here, the hybrid of the above GGABC and GABC methods is called the 3G-ABC algorithm for strong discovery and exploitation processes. …”
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2
Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar
Published 2015“…This research presents a modified optimization program for the system splitting problem in large scale power system based on Artificial Bee Colony algorithm and graph theory. …”
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3
Implementation of PID based controller tuned by Evolutionary Algorithm for Double Link Flexible Robotic Manipulator
Published 2018“…This signifies that, the PSO algorithm is very effective in optimizing the PID parameters.…”
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4
Minimizing the total cost of inventory by using artificial bee colony algorithm / Nurul Syakira Mohd Zin
Published 2022“…The algorithm characterised a swarm-based meta-heuristic algorithm comprised of three divisions of bee troops in the ABC model, namely employed, onlooker, and scout bees. …”
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Research Reports -
5
A Metaheuristic Optimization Using Explosion Method On A Hybrid Pd2-Lqr Quadcopter Controller
Published 2021“…Therefore, an optimization algorithm based on the explosion method called REA was proposed and implemented on the proposed Hybrid PD2-LQR control structure. …”
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6
Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…There is no particular study which focuses on the optimization and prediction of blades parameters using natural inspired algorithms namely Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and Adaptive Neuro-fuzzy Interface System (ANFIS) respectively for optimal power coefficient (�436�45D ). …”
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An Intelligent Modeling of Oil Consumption
Published 2015“…In this study, we select Middle East countries involving Jordan, Lebanon, Oman, and Saudi Arabia for modeling oil consumption based on computational intelligence methods. The limitations associated with Levenberg-Marquardt (LM) Neural Network (NN) motivated this research to optimize the parameters of NN through Artificial Bee Colony Algorithm (ABC-LM) to build a model for the prediction of oil consumption. …”
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Book Chapter -
8
System identification and control of linear electromechanical actuator using PI controller based metaheuristic approach
Published 2024“…While the PI controller is commonly used due to its simplicity and versatility in various control scenarios, its effectiveness is limited by its complex tuning process, which requires significant time and effort to achieve the optimal performance. …”
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System identification and control of linear electromechanical actuator using PI controller based metaheuristic approach
Published 2024“…While the PI controller is commonly used due to its simplicity and versatility in various control scenarios, its effectiveness is limited by its complex tuning process, which requires significant time and effort to achieve the optimal performance. …”
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10
Adaptive filtering of EEG/ERP through bounded range artificial Bee Colony (BR-ABC) algorithm
Published 2014“…A comparative study of the performance of conventional gradient based methods like LMS, RLS, and ABC algorithm is also made which reveals that ABC algorithm gives better performance in highly noisy environment.…”
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A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem
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Effectiveness of Nature-Inspired Algorithms using ANFIS for Blade Design Optimization and Wind Turbine Efficiency
Published 2019“…In addition, an adaptive neuro-fuzzy interface (ANFIS) approach is implemented to predict the Cp of wind turbine blades for investigation of algorithm performance based on the coefficient determination (R 2 ) and root mean square error (RMSE). …”
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13
Effectiveness of nature-inspired algorithms using ANFIS for blade design optimization and wind turbine efficiency
Published 2019“…In addition, an adaptive neuro-fuzzy interface (ANFIS) approach is implemented to predict the Cp of wind turbine blades for investigation of algorithm performance based on the coefficient determination (R2) and root mean square error (RMSE). …”
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14
Home buyer assistant using artificial bee colony algorithm / Muhammad Izzat Azri Azman
Published 2017“…The ABC algorithm is implemented to improve the recommendation accuracy. …”
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15
Multiobjective optimization using weighted sum Artificial Bee Colony algorithm for Load Frequency Control
Published 2014“…This paper presents the implementation of multiobjective based optimization of Artificial Bee Colony (ABC) algorithm for Load Frequency Control (LFC) on a two area interconnected reheat thermal power system. …”
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16
Minimizing the total cost of inventory by using artificial bee colony algorithm / Nurul Syakira Mohd Zin
Published 2021“…The algorithm characterised a swarm-based meta-heuristic algorithm comprised of three divisions of bee troops in the ABC model, namely employed, onlooker, and scout bees. …”
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Student Project -
17
Group method of data handling with artificial bee colony in combining forecasts
Published 2018“…This study is done by combining individual forecasts of Group Method of Data Handling models using the weighted-based combine approach. The weights for each individual model are calculated using ABC algorithm. …”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023Conference paper -
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Application of genetic algorithm methods to optimize flowshop sequencing problem
Published 2008“…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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Undergraduates Project Papers -
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Seamless vertical handover technique for vehicular ad-hoc networks using artificial bee colony-particle swarm optimisation
Published 2019“…The algorithm will process and calculate the required handover timing for each node in advance, based on the mobile nodes’ velocity and received signal strength to reduce the handover process latency. …”
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