Search Results - (( parameter optimization method algorithm ) OR ( wolf optimization strategy algorithm ))

Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost by Chen, Suihai, Bong, Chih How, Chiu, Po Chan

“…PSO-EBGWO is used to optimize the parameters of the CatBoost model. In this method, the Gray Wolf optimized algorithm (EBGWO) is further optimized by particle swarm optimization (PSO), and when combined with it, the convergence performance of the model is improved, the parameters of the model are reduced, and the model is simplified. …”
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Optimal performance of stand-alone hybrid microgrid systems based on integrated techno-economic-environmental energy management strategy using the grey wolf optimizer by Tukkee, Ahmed Sahib, Bin Abdul Wahab, Noor Izzri, Binti Mailah, Nashiren Farzilah, Hassan, Mohd Khair

“…Grey Wolf Optimizer (GWO) was utilized to find the optimal size of the hybrid Microgrid components and calculate the multi-objective function with and without the proposed management method. …”
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A novel MPPT approach for photovoltaic system using Pelican optimization and high-gain DC–DC converter by Akter, Khadiza, Motakabber, S. M. A., Alam, A. H. M. Zahirul, Yusoff, Siti Hajar, Pachauri, Rupendra Kumar, Malik, Hasmat, Jadoun, Vinay Kumar

“…An ideal PV model technique is employed in this study to accurately approximate the system’s mathematical parameters. The performance of the POA is benchmarked against three other Metaheuristics MPPT techniques: Particle Swarm Optimization (PSO), Harris Hawks Optimization (HHO),Gray Wolf Optimization (GWO), and Cuckoo Search (CS). …”
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Urban connected vehicle lane planning based on improved Frank Wolfe algorithm by Anqi, Jiang, Faziawati, Abdul Aziz, Norsidah, Ujang, Mohd Afzan, Mohamed

“…The results showed that the accuracy and recall of the proposed improved whale optimization algorithm on the Iris dataset were 95.27% and 92.65%, respectively, which were superior to traditional whale optimization algorithm, moth flame optimization algorithm, moth flame optimization algorithm combined with chaos strategy, and adaptive firefly optimization algorithm. …”
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Hybrid clustering-GWO-NARX neural network technique in predicting stock price by Das, Debashish, Sadiq, Ali Safa, Mirjalili, Seyedali, Noraziah, Ahmad

“…Consequently, this paper endeavours to determine an efficient stock prediction strategy by implementing a combinatorial method of Grey Wolf Optimizer (GWO), Clustering and Non Linear Autoregressive Exogenous (NARX) Technique. …”
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An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

“…Grey Wolf Optimizer (GWO) is a recently developed meta-heuristic algorithm which is appealing to researcher owing to its demonstrated performance as cited in the scientific literature. …”
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Grey wolf optimization for enhanced performance in wind power system with dual-star induction generators by Benamara K., Amimeur H., Hamoudi Y., Abdolrasol M.G.M., Cali U., Ustun T.S.

“…The primary objective is to optimize the entire system by fine-tuning PID and PI controllers through the application of meta-heuristic algorithms, specifically Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO). …”

Grey Wolf optimization based power management strategy for battery storage of dfig-wecs in standalone operating mode by Nasir Uddin M., Khairul Amin I., Rezaei N., Marsadek M.

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

“…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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Optimal sizing of autonomous hybrid microgrids with economic analysis using grey wolf optimizer technique by Tukkee, Ahmed Sahib, Abdul Wahab, Noor Izzri, Mailah, Nashiren Farzilah

“…Different configurations of hybrid Microgrids are proposed comprising various generating re�sources to meet the electrical load of small villages in Malaysia. Grey Wolf Optimizer (GWO) is employed to minimize the cost of energy COE (/kWh) considering operation constraints. …”
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CSGO: a game-inspired metaheuristic algorithm for global optimization by Rahman, Tuan A. Z., Md Rezali, Khairil Anas, As'arry, Azizan

“…This paper presents a video game-inspired meta-heuristic algorithm and its performance evaluation. This optimizer algorithm is developed by assembling impressive features of previous well-known optimizer algorithms such as stochastic fractal search (SFS), artificial gorilla troops optimizer (GTO) and marine predators algorithm (MPA) with addition of chaotic operators. …”
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Optimization and Control of Economic Dispatch for Power Systems by Ab Ghani, Mohd Ruddin

“…The formulation caters for loading and deloading rates, limits on generators outputs, spinning reserve requirements and group power import-export limits. The modelling strategy and solution techniques employed are based on Dantzig-Wolfe Decomposition principle, which produces a master problem solved by revised simplex method and a capacitated transshipment subproblem solved by network flow algorithm. …”
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Optimal power flow with renewable power generations using hyper-heuristic technique by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…The technique selects and integrates the strengths of three low-level meta-heuristics algorithms, including Grey Wolf Optimizer (GWO), Barnacles Mating Optimizer (BMO), and Whale Optimization Algorithm (WOA), to achieve the best possible results. …”
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Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

“…BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
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A performance of AFIRO among asynchronous iteration strategy metaheuristic algorithms by Ab Rahman, Tasiransurini, Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim

“…In the original paper, AFIRO was compared with the Particle Swarm Optimisation algorithm, Genetic Algorithm, and Grey Wolf Optimizer. …”
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Adaptive Switching Gravitational Search Algorithm: An Attempt To Improve Diversity Of Gravitational Search Algorithm Through Its Iteration Strategy by Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim, Marizan, Mubin, Shahdan, Sudin

“…The proposed ASw-GSA is also compared to original GSA, particle swarm optimization (PSO), genetic algorithm (GA), bat-inspired algorithm (BA) and grey wolf optimizer (GWO). …”
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A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

“…To examine the effectiveness of proposed method, four recent and popular feature selection methods namely BPSO, genetic algorithm (GA), binary gravitational search algorithm (BGSA) and competitive binary grey wolf optimizer (CBGWO) are used in a performance comparison. …”
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Energy management system for optimal operation of microgrid consisting of PV, fuel cell and battery / Shivashankar Sukumar by Shivashankar , Sukumar

“…The BESS sizing problem is solved using grey wolf optimizer (GWO), particle swarm optimization (PSO), artificial bee colony (ABC), gravitational search algorithm (GSA), and genetic algorithm (GA). …”
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Unleashing the power of Manta Rays Foraging Optimizer: A novel approach for hyper-parameter optimization in skin cancer classification by Adamu, Shamsuddeen, Alhussian, Hitham, Aziz, Norshakirah, Abdulkadir, Said Jadid, Alwadin, Ayed, Abdullahi, Mujaheed, Garba, Aliyu

“…Empirical evaluations on diverse datasets (ISIC, PH2, HAM10000) showcase the significant superiority of the MRFO-based model over conventional optimization algorithms. The model achieves impressive accuracy and loss metrics (ISIC: 99.43 , 0.0250; PH2: 99.96 , 0.0033; HAM10000: 97.70 , 0.0626), outperforming alternative optimization algorithms such as the Grey Wolf Optimizer (98.33 accuracy, 0.17 loss), Whale Optimization Algorithm (96 accuracy), Grasshopper Optimization Algorithm (97.2 accuracy), Densnet121-MRFO (99.26 accuracy), InceptionV3 with GA (99.9 accuracy), and African Vulture Optimization Algorithm (92.7 accuracy). …”
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Cho, Bo Wen

“…Improved mean fitness function values were also revealed in the TRS (11.63%) and EMPS (69.63%) assessments, surpassing the conventional algorithm. This proposed algorithm produced solutions with superior accuracy and consistency compared to various established metaheuristic strategies, including particle swarm optimizer, grey wolf optimizer, multi-verse optimizer, AOA, and a hybrid optimizer (average multi-verse optimizer-sine-cosine algorithm).…”
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