Search Results - (( simulation optimization bees algorithm ) OR ( based implementation using algorithm ))

Multiobjective optimization using weighted sum Artificial Bee Colony algorithm for Load Frequency Control by Naidu, K., Mokhlis, Hazlie, Bakar, Ab Halim Abu

“…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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The design and applications of the african buffalo algorithm for general optimization problems by Odili, Julius Beneoluchi

“…Some of the successfully designed stochastic algorithms include Simulated Annealing, Genetic Algorithm, Ant Colony Optimization, Particle Swarm Optimization, Bee Colony Optimization, Artificial Bee Colony Optimization, Firefly Optimization etc. …”
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Deterministic static sensor node placement in wireless sensor network based on territorial predator scent marking behavior by Abidin H.Z., Din N.M., Radzi N.A.M.

“…A simulation study has been carried out to compare the performance of the proposed algorithm implemented in two different single objective approaches with an Integer Linear Programming based algorithm and another biological inspired algorithm. …”

Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm by Mohammed Abdullah, Abdullah Nasser

“…In line with the emerging field called Search based Software Engineering, many recently developed t-way strategies have adopted meta-heuristic algorithms as the basis of their implementations such as Simulated Annealing, Genetic Algorithm, Ant Colony Optimization Algorithm, Particle Swarm Optimization, Harmony Search and Cuckoo Search, owing their superior performance in term of test size reduction as compared to general computational based strategies, such as General t-way, Test Vector Generator, In Parameter Order General, Jenny, and Automatic Efficient Test Generator. …”
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Solving large-scale problems using multi-swarm particle swarm approach by Salih, Sinan Q., Alsewari, Abdulrahman A.

“…The results showed that the proposed PSO algorithm outperformed the other algorithms in terms of the optimal solutions and the convergence.…”
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Transmission loss minimization using SVC based on particle swarm optimization by Jumaat, S.A., Musirin, I., Othman, M.M., Mokhlis, Hazlie

“…Validation through the implementation on the IEEE 26-bus system shows that the PSO is found feasible to achieve the task. The simulations results are compared with those obtained from the Bee Algorithm (BA) technique in the attempt to highlight its merit.…”
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

“…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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A new teaching learning artificial bee colony based maximum power point tracking approach for assessing various parameters of photovoltaic system under different atmospheric condit... by Dokala Janandra, Krishna Kishore

“…Hence, to optimize the cost of integrating RES‘s through newly developed maximum power point tracking (MPPT) based optimization method such as grasshopper optimization algorithm (GOA) has been introduced. …”
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Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain by Hussain, Muhamad Hatta

“…The Electric Transient and Analysis Program (ETAP) was used as the simulation tool, while Matrices Laboratory (MATLAB) was utilized to implement all the algorithms in this study. …”
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Methane plume localization with enhanced self-best reduction and Gaussian improved particle swarm optimization (GiPSO) by Liew, Jia Hun

“…Adapting the Gaussian gas plume model in the simulation provides the experiment with a realistic optimization problem for GiPSO to optimize in the simulation, where we can test the engagement of dynamically challenging optimization problems such as gas plume dispersions. …”
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Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System by Wang, Chen, Wood, Lincoln Christopher, Li, Heng, Aw, Zhenye, Keshavarzsaleh, Abolfazl

“…This study aims to develop a fire evacuation routing model "Bee-Fire" using artificial bee colony optimization (BCO) and to test the routing model through a simulation run. …”
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An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

“…The simulation results of the MLP trained with improved algorithms were compared with that when trained with the standard BP, ABC, Global ABC and Particle Swarm Optimization algorithm. …”
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Optimization of drilling path using the bees algorithm by Kamaruddin, Shafie, Rosdi, Mohamad Naqiuddin, Sukindar, Nor Aiman

“…The results comparison shows that the Bees Algorithm achieved comparable performance compared to other algorithms.…”
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System performances analysis of reservoir optimization�simulation model in application of artificial bee colony algorithm by Hossain M.S., El-Shafie A., Mahzabin M.S., Zawawi M.H.

Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib by Dian Najihah , Abu Talib

“…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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System identification and control of linear electromechanical actuator using PI controller based metaheuristic approach by Abdullah Hashim, Azrul Azim, Abdul Ghani, Nor Maniha, Ahmad, Salmiah, Nasir, Ahmad Nor Kasruddin

“…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. To address this issue, the paper focuses on employing metaheuristic approaches that are Spiral Dynamic Algorithm (SDA) and Artificial Bee Colony (ABC) to fine tune the PI parameters for controlling the position of EMA. …”
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System identification and control of linear electromechanical actuator using PI controller based metaheuristic approach by Azrul Azim, Abdullah Hashim, Nor Maniha, Abdul Ghani, Salmiah, Ahmad, Ahmad Nor Kasruddin, Nasir

“…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. To address this issue, the paper focuses on employing metaheuristic approaches that are Spiral Dynamic Algorithm (SDA) and Artificial Bee Colony (ABC) to fine tune the PI parameters for controlling the position of EMA. …”
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Bees algorithm for Forest transportation planning optimization in Malaysia by Jamaluddin, Jamhuri, Kamarudin, Norizah, Ismail, Mohd Hasmadi, Ahmad, Siti Azfanizam

“…Examples of algorithm that are finding their way to the forest transportation planning problem include Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm, Simulated Annealing (SA) algorithm and Tabu Search (TS) algorithm. …”
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Performance Enhancement Of Artificial Bee Colony Optimization Algorithm by Abro, Abdul Ghani

“…Artificial Bee Colony (ABC) algorithm is a recently proposed bio-inspired optimization algorithm, simulating foraging phenomenon of honeybees. …”
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Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway by Ahmad Muhaimin, Ismail, Muhammad Akmal, Remli, Yee Wen, Choon, Nurul Athirah, Nasarudin, Norsyahidatul Nazirah, Ismail, Mohd Arfian, Ismail, Mohd Saberi, Mohamad

“…The experimental results show that ABC outperforms other estimation algorithms and gives more accurate kinetic parameter values for the simulated model. …”
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