Search Results - optimal ((((llc algorithm) OR (acs algorithm))) OR (_ algorithm))

Energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: A review by Oladosu T.L., Pasupuleti J., Kiong T.S., Koh S.P.J., Yusaf T.

“…Therefore, this study presents the prospect of artificial intelligence-based algorithms, control systems, and energy management strategies advances on HFCEVs performance optimization. …”

Ant colony optimization in dynamic environments by Chen, Fei Huang

“…Apart from the size of the optimization problem, how the swapping interval affects the dynamic optimization by the ant algorithms is also investigated. …”
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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis by Tubishat, Mohammad, Abushariah, Mohammad A.M., Idris, Norisma, Aljarah, Ibrahim

“…In SA, feature selection phase is an important phase for machine learning classifiers specifically when the datasets used in training is huge. Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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Performance Comparison of FA, PSO and CS application in SINR Optimisation for LCMV Beamforming Technique by Doroody C., Kiong T.S.

“…Beamforming; Bioluminescence; Fire protection; MATLAB; Signal interference; Spurious signal noise; Beamforming technique; Firefly algorithms; LCMV; Meta heuristic algorithm; Nature inspired algorithms; Optimisations; Particle swarm optimisation; Performance comparison; Particle swarm optimization (PSO)…”

Path Optimization For Cooperative Multi-Head 3d Printing by Cheong, Kah Jun

“…Therefore, to solve the LPOP, two algorithms are proposed, the modified AS algorithm and the modified ACS algorithm. …”
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Balancing exploration and exploitation in ACS algorithms for data clustering by Jabbar, Ayad Mohammed, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

“…Ant colony optimization (ACO) is a swarm algorithm inspired by different behaviors of ants. …”
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A Comparative Study on Optimal Design of LLC Resonant Converter by Intelligent Optimization Techniques by K. S. , Rama Rao, Azhar, Nur Syahirah Mohd, Hamid, Nor Hisham

“…Three evolutionary optimization techniques viz., Scatter Search (SS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are employed to derive the optimal control parameters of the resonant converter and the results obtained are compared in terms of efficiency. …”
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A genetic algorithm for solving supply chain network design model by Firoozi, Zahra, Ismail, Napsiah, Ariafar, Shahram, Tang, Sai Hong, Mohd Ariffin, Mohd Khairol Anuar

“…Computational results are presented to show the algorithm performance.…”
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A speech recognition system based on structure equivalent fuzzy neural network trained by firefly algorithm by Tahereh Hassanzadeh, Karim Faez, Golnaz Seyfi

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An Experiment of Ant Algorithms : Case Study of Kota Kinabalu Central Town by Nor Rafidah, Mohamad

“…The objectives of this study are to explore and evaluate the Ant System (AS) algorithm and Ant Colony System (ACS) algorithm in finding shortest paths. …”
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A swarm-based artificial immune system for solving multimodal functions by Yap D.F.W., Koh S.P., Tiong S.K., Prajindra S.K.

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Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network by Husna, Jamal Abdul Nasir

“…Swarm intelligence algorithms have been applied in solving these problems including the Ant Colony System (ACS) which is one of the ant colony optimization variants. …”
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Modified ACS centroid memory for data clustering by Jabbar, Ayad Mohammed, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

“…Ant Colony Optimization for Clustering (ACOC) is a swarm algorithm inspired from nature to solve clustering issues as optimization problems. …”
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Embedding Malaysian House Red Ant Behavior into an Ant Colony System by Ali Othman, Zulaiha, Md Rais, Helmi, Hamdan, Abdul Razak

“…This research aims to improve the algorithm by embedding individual Malaysian House Red Ant behavior into ACS. …”
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New heuristic function in ant colony system for the travelling salesman problem by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

“…Ant Colony System (ACS) is one of the best algorithms to solve NP-hard problems.However, ACS suffers from pheromone stagnation problem when all ants converge quickly on one sub-optimal solution.ACS algorithm utilizes the value between nodes as heuristic values to calculate the probability of choosing the next node. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

“…Recently, in line with the upcoming field called Search based Software Engineering (SBSE), many newly strategies have been developed adopting specific optimization algorithm (e.g. Genetic Algorithm (GA), Ant Colony (AC), Simulated Annealling (SA), Particle Swarm Optimization, and Harmony Search Algorithm (HS) as their basis in an effort to generate the most optimal solution. …”
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A comparison on PSO variants in calculating HEPWM switching angles for a cascaded H-bridge multilevel inverter by Norkharziana, Mohd Nayan, Naziha, Ahmad Azli, Dr., Sharin, Md Ayob, Dr.

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Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…Thus, seven metaheuristic algorithms: Barnacles Mating Optimizer (BMO), Marine Predators Algorithm (MPA), Moth–Flame Optimization (MFO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching–Learning-Based Optimization (TLBO) and Heap-Based Optimizer (HBO) are used to solve two objective functions: power loss and cost minimizations. …”
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Scheduling jobs in computational grid using hybrid ACS and GA approach by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

“…Metaheuristics algorithms show very good performance in solving various job scheduling problems in computational grid systems.However, due to the complexity and heterogeneous nature of resources in grid computing, stand-alone algorithm is not capable to find a good quality solution in reasonable time.This study proposes a hybrid algorithm, specifically ant colony system and genetic algorithm to solve the job scheduling problem.The high level hybridization algorithm will keep the identity of each algorithm in performing the scheduling task.The study focuses on static grid computing environment and the metrics for optimization are the makespan and flowtime.Experiment results show that the proposed algorithm outperforms other stand-alone algorithms such as ant system, genetic algorithms, and ant colony system for makespan.However, for flowtime, ant system and genetic algorithm perform better.…”
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Firefly algorithm-based neural network for GCPV system output prediction: article / Nor Syakila Mohd Zainol Abidin by Mohd Zainol Abidin, Nor Syakila

“…In the proposed MLFNN, Firefly Algorithm (FA) was employed as the optimizer and search tools of the MLFNN training parameters. …”
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