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421
Salp Swarm Algorithm for Node Localization in Wireless Sensor Networks
Published 2019-01-01“…In this paper, a node localization scheme is proposed based on a recent bioinspired algorithm called Salp Swarm Algorithm (SSA). The proposed algorithm is compared to well-known optimization algorithms, namely, particle swarm optimization (PSO), Butterfly optimization algorithm (BOA), firefly algorithm (FA), and grey wolf optimizer (GWO) under different WSN deployments. …”
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422
Multijunction solar cell parameter estimation based on metaheuristic algorithms
Published 2025-03-01“…The study compared the performance of five optimization algorithms: Grey Wolf Optimizer (GWO), Artificial Hummingbird Algorithm (AHA), Tunicate Swarm Algorithm (TSA), War Strategy Algorithm (WSA), and Moth flam optimizer (MFO). …”
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423
CEEMDAN-IHO-SVM: A Machine Learning Research Model for Valve Leak Diagnosis
Published 2025-03-01“…Moreover, the performance of IHO was proven to be optimal compared to HO, Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), and Sparrow Search Algorithm (SSA) by calculating twelve test functions. …”
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424
Water Quality Prediction Based on Hybrid Deep Learning Algorithm
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425
DATA DRIVEN RULE-BASED PEAK SHAVING ALGORITHM FOR SCHEDULING REFRIGERATORS
Published 2024-12-01“…In the day-ahead mode, Long Short-Term Memory (LSTM) neural networks are utilized to forecast demand and generation. A Parameter tuned Grey Wolf Optimizer (GWOP) is proposed and employed to determine the optimal generation for the initial timestep of the scheduling period. …”
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426
Machine learning prediction and explainability analysis of high strength glass powder concrete using SHAP PDP and ICE
Published 2025-07-01“…To further enhance performance, XGB was optimized using Particle Swarm Optimization (PSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO). …”
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427
Personnel Scheduling Problem under Hierarchical Management Based on Intelligent Algorithm
Published 2021-01-01“…Two hybrid heuristic algorithms based on multiobjective grey wolf optimizer (MOGWO) and three corresponding single heuristic algorithms are employed to solve this problem. …”
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428
Numerical Solution of Dual Fully Fuzzy Equations System Using Some Meta Heuristic Methods
Published 2025-10-01“…Here we compare the performance of four meta-heuristic methods, i.e., genetic algorithm (GA), chaos optimization algorithm (COA), particle swarm optimization (PSO), and grey wolf optimizer (GWO), to solve some cases in our problems. …”
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429
Real-time congestion control using cascaded LSTM deep neural networks for deregulated power markets
Published 2025-08-01“…The LSTM-DNN was trained using data from a grey wolf optimization (GWO). This method provides a rapid solution with approximately 98% accuracy for managing congestion in the spot power market. …”
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430
A novel economic load dispatch method of microgrid based on hybrid slime mould and genetic algorithm
Published 2025-07-01“…For performance evaluation, GSMA is compared with slime mould algorithm (SMA), grey wolf optimizer (GWO), sparrow search algorithm (SSA), Harris Hawks optimization (HHO), whale optimization algorithm (WOA) and particle swarm optimization (PSO) using standard optimization functions. …”
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431
F3TM: Flooding Factor based Trust Management Framework for secure data transmission in MANETs
Published 2017-07-01“…True flooding approach is utilized to identify attacker nodes based on the calculation of trust value. Route Discovery Algorithm is developed to discover an efficient and secure path for data forwarding using Experimental Grey Wolf algorithm for validating network nodes. …”
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432
Predicting the shield effectiveness of carbon fiber reinforced mortars utilizing metaheuristic algorithms
Published 2025-07-01“…Specifically, support vector regression (SVR) was combined with three optimization algorithms: firefly algorithm (FFA), particle swarm optimization (PSO), and grey wolf optimization (GWO) to create hybrid models for estimating the SE of carbon fiber-reinforced mortars. …”
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433
Improving frequency and voltage performance in interconnected microgrids using virtual inertial control
Published 2025-09-01“…The outcomes of the proposed method are compared with those of TLBO, whale optimization algorithm (WOA), grey wolf optimization (GWO), differential evolution (DE), and RCGA to assess the effectiveness of the proposed method. …”
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434
An explainable analytical approach to heart attack detection using biomarkers and nature-inspired algorithms
Published 2025-12-01“…Mutual information achieved a maximum testing accuracy of 90 % and highest precision of 94 %. The Whale Optimization Algorithm, Jaya Algorithm, Grey Wolf Optimizer and Sine Cosine Algorithm were the next best performing algorithms. …”
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435
Multi-objective quantum hybrid evolutionary algorithms for enhancing quality-of-service in internet of things
Published 2025-04-01“…To address these issues, we introduce a quantum-inspired hybrid algorithm that combines the strengths of Multi-Objective Grey Wolf Optimization Algorithm (MOGWOA) and Multi-Objective Whale Optimization Algorithm (MOWOA), enhanced with quantum principles. …”
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436
Enhancing network lifetime in WSNs through coot algorithm-based energy management model
Published 2025-06-01“…To improve the performance of Wireless Sensor Networks (WSN), this study offers a novel energy-efficient clustering and routing technique based on the Coot Optimization Algorithm (COA). This addresses issues such as high energy consumption, communication delays, and security.To ensure energy savings and network reliability, the fitness function evaluates cluster heads and best routes based on constraints.COOT outperforms other Metaheuristics Algorithms like Butterfly Optimization Algorithm, Genetic Algorithm, Tunicate Swarm Gray Wolf Optimization Algorithm, and Bird Swarm Algorithm in simulation with performance measurements and enhancing network functionality and protection.Key methodology points include: • Proposed a multiple constraints clustering and routing technique using COAto solve the most crucial issues that arise in WSNs. • Integrated an advanced fitness function that determines cluster head selection, and the routing path based on residual energy, delay, security, trust, distance, and link quality so that energy load is evenly distributed and credible data flow is maintained across the network and made Innovative and Effective Solution. • Proven Results Demonstrated superior network performance, achieving the lowest delay, highest network lifetime (3571 rounds) and enhanced security (0.8) and trust (0.6) compared to existing algorithms with less energy consumption, making it the most suitable solution for WSN performance improvement.…”
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437
Performance Evaluation of Hybrid Bio-Inspired and Deep Learning Algorithms in Gene Selection and Cancer Classification
Published 2025-01-01“…Our findings reveal that hybrid bio-inspired methods, such as Grey Wolf Optimizer and Harris Hawks Optimization, achieve high classification accuracy with minimal selected genes, making them computationally efficient for clinical applications. …”
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438
Ensemble machine learning algorithm for cost-effective and timely detection of diabetes in Maiduguri, Borno State
Published 2024-09-01“…The proposed WAEL model ingeniously combines five feature spaces through the grey wolf optimisation (GWO) algorithm to uncover the optimal weight combination. …”
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439
Distributed hybrid energy storage photovoltaic microgrid control based on MPPT algorithm and equilibrium control strategy
Published 2024-12-01“…The novelty of this study is that the improved Grey Wolf optimization algorithm enhances the global search ability by introducing the random jump mechanism of Levy flight algorithm and the combination of particle swarm optimization algorithm and Grey Wolf optimization algorithm to avoid falling into the local optimal. …”
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440
An Improved Extreme Learning Machine (ELM) Algorithm for Intent Recognition of Transfemoral Amputees With Powered Knee Prosthesis
Published 2024-01-01“…Additionally, a hybrid grey wolf optimization and slime mould algorithm (GWO-SMA) is proposed to optimize the hidden layer bias of the improved ELM classifier. …”
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