Harmonics management and hosting capacity enhancement: Optimal double-resistor damped double-tuned power filter with artificial hummingbird optimization DOI Creative Commons
Mohammed M. Alhaider, Shady H. E. Abdel Aleem, Ziad M. Ali

et al.

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(5), P. e0303207 - e0303207

Published: May 10, 2024

This paper introduces a novel and improved double-resistor damped double-tuned passive power filter (DR-DDTF), designed using multi-objective optimization algorithms to mitigate harmonics increase the hosting capacity of distribution systems with distributed energy resources. Although four different topologies single-resistor filters (DDTFs) have been studied before in literature, effectiveness two DR-DDTF configurations has not examined. work redresses this gap by demonstrating that via comprehensive simulations on systems, provides better harmonic suppression resonance mitigation than alternatives. When it comes optimizing for maximum minimum system active losses, artificial hummingbird outperformed six other benchmark. To allow higher penetration generation without requiring grid upgrades, newly developed good alternative.

Language: Английский

Botox Optimization Algorithm: A New Human-Based Metaheuristic Algorithm for Solving Optimization Problems DOI Creative Commons
Marie Hubálovská, Štěpán Hubálovský, Pavel Trojovský

et al.

Biomimetics, Journal Year: 2024, Volume and Issue: 9(3), P. 137 - 137

Published: Feb. 23, 2024

This paper introduces the Botox Optimization Algorithm (BOA), a novel metaheuristic inspired by operation mechanism. The algorithm is designed to address optimization problems, utilizing human-based approach. Taking cues from procedures, where defects are targeted and treated enhance beauty, BOA formulated mathematically modeled. Evaluation on CEC 2017 test suite showcases BOA’s ability balance exploration exploitation, delivering competitive solutions. Comparative analysis against twelve well-known algorithms demonstrates superior performance across various benchmark functions, with statistically significant advantages. Moreover, application constrained problems 2011 highlights effectiveness in real-world tasks.

Language: Английский

Citations

17
Fungal growth optimizer: A novel nature-inspired metaheuristic algorithm for stochastic optimization DOI

Mohamed Abdel‐Basset,

Reda Mohamed, Mohamed Abouhawwash

et al.

Computer Methods in Applied Mechanics and Engineering, Journal Year: 2025, Volume and Issue: 437, P. 117825 - 117825

Published: Feb. 9, 2025

Language: Английский

Citations

3
QSHO: Quantum spotted hyena optimizer for global optimization DOI Creative Commons
Tapas Si, Péricles Miranda, Utpal Nandi

et al.

Artificial Intelligence Review, Journal Year: 2025, Volume and Issue: 58(3)

Published: Jan. 6, 2025

Spotted Hyena Optimizer (SHO) is a population-based metaheuristic algorithm inspired by the spotted hyenas' social behavior, and it has been developed to solve global optimization problems. SHO shown superior performance over its competitive algorithms in solving benchmark function engineering design However, suffers from getting stuck local optima due lack of exploration while multi-modal This article proposes an improved SHO, quantum (QSHO), computing. The QSHO implements computing mechanism promote ability. novel method tested on well-known IEEE CEC2013 CEC2017 suits with 30 50 dimensions four real-world results are compared that Classical (ISHO), Modified (MSHO), Oppositional mutation operator (OBL-MO-SHO), space transformation search (STS-SHO), Quantum Salp Swarm Algorithm (QSSA), Chimp Optimization (ChOA). analyzed using Wilcoxon Signed Rank Test (WSRT) Friedman Test. empirical show statistically outperforms other for problem dimensions. According statistics, ranked first second 30D 50D, respectively, whereas both 50D. In addition, we have assessed problems, algorithms.

Language: Английский

Citations

2
Dollmaker Optimization Algorithm: A Novel Human-Inspired Optimizer for Solving Optimization Problems DOI Open Access

Saleh Al Omari,

Khalid Kaabneh,

I. Abu-Falahah

et al.

International journal of intelligent engineering and systems, Journal Year: 2024, Volume and Issue: 17(3), P. 816 - 828

Published: May 3, 2024

In this article, a new human-based metaheuristic algorithm named Dollmaker Optimization Algorithm (DOA) is introduced, which imitates the strategy and skill of dollmaker when making dolls.The basic inspiration DOA derived from two natural behaviors in doll process (i) general changes to dollmaking materials (ii) precise small on appearance characteristics theory proposed then modeled mathematically phases exploration based simulation large made doll-making exploitation performance optimization evaluated twenty-three standard benchmark functions unimodal, high-dimensional multimodal, fixed-dimensional multimodal types.The results show that has achieved suitable for problems with its ability exploration, exploitation, balance them during search process.Comparison twelve competing algorithms shows superior compared by providing better all getting rank first best optimizer.In addition, efficiency handling real-world applications four engineering design problems.Simulation acceptable real world values variables objective algorithms.

Language: Английский

Citations

16
Hybrid Adam_POA: Hybrid Adam_Pufferfish Optimization Algorithm Based Load Balancing in Cloud Computing DOI
Sandeep Kumar Hegde,

Rajalaxmi Hegde,

Chetan Kumar

et al.

SN Computer Science, Journal Year: 2025, Volume and Issue: 6(2)

Published: Feb. 15, 2025

Language: Английский

Citations

1
An integrative TLBO-driven hybrid grey wolf optimizer for the efficient resolution of multi-dimensional, nonlinear engineering problems DOI Creative Commons

Harleenpal Singh,

Sobhit Saxena, Himanshu Sharma

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 2, 2025

Language: Английский

Citations

1
Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration Versus Algorithmic Behavior, Critical Analysis Recommendations DOI
Daniel Molina, Javier Poyatos, Javier Del Ser

et al.

Cognitive Computation, Journal Year: 2020, Volume and Issue: 12(5), P. 897 - 939

Published: July 5, 2020

Language: Английский

Citations

41
Design and Development of Grid Connected Renewable Energy System for Electric Vehicle Loads in Taif, Kingdom of Saudi Arabia DOI Creative Commons
Mohd Bilal, Pitshou N. Bokoro, Gulshan Sharma

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(16), P. 4088 - 4088

Published: Aug. 17, 2024

Globally, the integration of electric vehicles (EVs) in transportation sector represents a significant step towards achieving environmental decarbonization. This shift also introduces new demand for power within utility grid network. study focuses on design and development grid-connected renewable energy system tailored to meet EV load demands Taif, Kingdom Saudi Arabia (KSA). The sources, specifically solar photovoltaic (SPV) wind turbines (WT), is explored context economic feasibility reliability. Key considerations include optimizing efficiently handle fluctuating charging while minimizing reliance conventional power. Economic analyses reliability assessments are conducted evaluate performance proposed system. article discusses technical sizing hybrid systems, reduction, net present cost selected location. A rigorous sensitivity analysis performed determine impact major variables such as inflation rate, real discount irradiation, Lack Power Supply Probability (LPSP) performance. results demonstrate that Pufferfish Optimization Algorithm (PFO) significantly outperforms other metaheuristic algorithms documented literature, well HOMER software. found best option operating stations at findings underscore potential sustainable solutions urban environments like highlighting importance integrating technologies growing with enhanced efficiency initiative seeks pave way greener more resilient infrastructure, aligning global efforts clean solutions.

Language: Английский

Citations

4
A novel cheetah optimizer hybrid approach based on opposition-based learning (OBL) and diversity metrics DOI
Erik Cuevas,

Oscar Barba,

Héctor Escobar

et al.

Computing, Journal Year: 2025, Volume and Issue: 107(2)

Published: Jan. 27, 2025

Language: Английский

Citations

0
Dynamic feature selection and quantum representation for precise heart disease prediction: Quantum-HeartDiseaseNet approach DOI

Liza M Kunjachen,

R. Kavitha

Computer Methods in Biomechanics & Biomedical Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 22

Published: Feb. 5, 2025

Cardiovascular disease is a leading cause of mortality, necessitating early and precise prediction for improved patient outcomes. This study proposes Quantum-HeartDiseaseNet, novel heart risk framework that integrates Dynamic Opposite Pufferfish Optimization Algorithm feature selection Quantum Attention-based Bidirectional Gated Recurrent Unit (QABiGRU) accurate diagnosis. The method enhances diagnosis accuracy while reducing dimensionality, Synthetic Minority Oversampling Technique (SMOTE) addresses data imbalance. Evaluated on three datasets, the proposed model achieved 98.87% accuracy, 98.74% precision, 98.56% recall, outperforming conventional methods. Experimental results validate its effectiveness in prediction.

Language: Английский

Citations

0