Quantum Marine Predator Algorithm: A Quantum Leap in Photovoltaic Efficiency Under Dynamic Conditions DOI Creative Commons
Okba Fergani, Yassine Himeur,

Raihane Mechgoug

и другие.

Information, Год журнала: 2024, Номер 15(11), С. 692 - 692

Опубликована: Ноя. 3, 2024

The Quantum Marine Predator Algorithm (QMPA) presents a groundbreaking solution to the inherent limitations of conventional Maximum Power Point Tracking (MPPT) techniques in photovoltaic systems. These limitations, such as sluggish response times and inadequate adaptability environmental fluctuations, are particularly pronounced regions with challenging weather patterns like Sunderland. QMPA emerges formidable contender by seamlessly integrating sophisticated hunting tactics marine predators principles quantum mechanics. This amalgamation not only enhances operational efficiency but also addresses need for real-time adaptability. One most striking advantages is its remarkable improvement time Compared traditional MPPT methods, which often struggle keep pace rapidly changing factors, demonstrates significant reduction time, resulting up 30% increase under fluctuating irradiance conditions resistive load 100 Ω. findings derived from extensive experimentation using NASA’s worldwide power prediction data. Through detailed comparative analysis existing methodologies, consistently outperforms counterparts, exhibiting superior stability across varying scenarios. By substantiating claims concrete data measurable improvements, this research transcends generic assertions establishes tangible advancement technology.

Язык: Английский

Sustainable Electrification—Advances and Challenges in Electrical-Distribution Networks: A Review DOI Open Access
Jimmy Gallegos, Paúl Arévalo, Christian Montaleza

и другие.

Sustainability, Год журнала: 2024, Номер 16(2), С. 698 - 698

Опубликована: Янв. 12, 2024

This paper provides a thorough exploration of the evolution and contemporary trends in electrical-distribution networks, with focus on smart grids context Industry 4.0. Beginning traditional components electrical grids, study highlights transition towards sustainable energy sources integration renewables. Key include economic operation, application distributed resources, significance photovoltaic solar energy. The unfolds seven sections, examining smart-electrical-network architecture, technology progression, efficiency, carbon-emission-reduction challenges, future perspectives, concluding insights. Each section delves into specific layers aspects, such as data management, infrastructure, automation, consumer interaction. intricate role meters their impact management is explored, providing comprehensive overview current state directions networks.

Язык: Английский

Процитировано

29
Enhanced marine predator algorithm for global optimization and engineering design problems DOI
Salih Berkan Aydemı̇r

Advances in Engineering Software, Год журнала: 2023, Номер 184, С. 103517 - 103517

Опубликована: Июнь 28, 2023

Язык: Английский

Процитировано

28
WBM-DLNets: Wrapper-Based Metaheuristic Deep Learning Networks Feature Optimization for Enhancing Brain Tumor Detection DOI Creative Commons
Muhammad Umair Ali, Shaik Javeed Hussain, Amad Zafar

и другие.

Bioengineering, Год журнала: 2023, Номер 10(4), С. 475 - 475

Опубликована: Апрель 14, 2023

This study presents wrapper-based metaheuristic deep learning networks (WBM-DLNets) feature optimization algorithms for brain tumor diagnosis using magnetic resonance imaging. Herein, 16 pretrained are used to compute the features. Eight algorithms, namely, marine predator algorithm, atom search algorithm (ASOA), Harris hawks butterfly whale grey wolf (GWOA), bat and firefly evaluate classification performance a support vector machine (SVM)-based cost function. A deep-learning network selection approach is applied determine best network. Finally, all features of concatenated train SVM model. The proposed WBM-DLNets validated based on an available online dataset. results reveal that accuracy significantly improved by utilizing selected relative those obtained full set DenseNet-201-GWOA EfficientNet-b0-ASOA yield results, with 95.7%. Additionally, compared reported in literature.

Язык: Английский

Процитировано

23
A parallel compact Marine Predators Algorithm applied in time series prediction of Backpropagation neural network (BNN) and engineering optimization DOI
Jeng‐Shyang Pan, Z. Zhang, Shu‐Chuan Chu

и другие.

Mathematics and Computers in Simulation, Год журнала: 2024, Номер 220, С. 65 - 88

Опубликована: Янв. 19, 2024

Язык: Английский

Процитировано

10
Optimizing Gaussian process regression (GPR) hyperparameters with three metaheuristic algorithms for viscosity prediction of suspensions containing microencapsulated PCMs DOI Creative Commons
Tao Hai, Ali Basem, As’ad Alizadeh

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Авг. 31, 2024

Abstract Suspensions containing microencapsulated phase change materials (MPCMs) play a crucial role in thermal energy storage (TES) systems and have applications building materials, textiles, cooling systems. This study focuses on accurately predicting the dynamic viscosity, critical thermophysical property, of suspensions MPCMs MXene particles using Gaussian process regression (GPR). Twelve hyperparameters (HPs) GPR are analyzed separately classified into three groups based their importance. Three metaheuristic algorithms, namely genetic algorithm (GA), particle swarm optimization (PSO), marine predators (MPA), employed to optimize HPs. Optimizing four most significant (covariance function, basis standardization, sigma) within first group any algorithms resulted excellent outcomes. All achieved reasonable R-value (0.9983), demonstrating effectiveness this context. The second explored impact including additional, moderate-significant HPs, such as fit method, predict method optimizer. While resulting models showed some improvement over group, PSO-based model exhibited noteworthy enhancement, achieving higher (0.99834). Finally, third was examine potential interactions between all twelve comprehensive approach, employing GA, yielded an optimized with highest level target compliance, reflected by impressive 0.999224. developed cost-effective efficient solution reduce laboratory costs for various systems, from TES management.

Язык: Английский

Процитировано

10
Recent Developments in Equilibrium Optimizer Algorithm: Its Variants and Applications DOI Open Access
Rebika Rai, Krishna Gopal Dhal

Archives of Computational Methods in Engineering, Год журнала: 2023, Номер 30(6), С. 3791 - 3844

Опубликована: Апрель 12, 2023

Язык: Английский

Процитировано

20
Analysis of Marine Predators Algorithm using BIAS toolbox and Generalized Signature Test DOI Creative Commons

Manish Kumar,

Kanchan Rajwar, Kusum Deep

и другие.

Alexandria Engineering Journal, Год журнала: 2024, Номер 95, С. 38 - 49

Опубликована: Март 29, 2024

The Marine Predators Algorithm (MPA) is a prominent Nature-Inspired Optimization (NIOA) that has garnered significant research interest due to its effectiveness. It draws inspiration from the foraging behaviors of marine predators, predominantly using Lévy or Brownian approach for strategy. Despite acclaim, structural bias within MPA not been thoroughly investigated, marking gap in current research. This absence targeted forms core rationale behind initiating this study. Structural recently identified NIOAs, causing population revisit specific regions search space without gaining new information. As result, it may lead increased computational costs and slow down rate convergence. Therefore, identifying essential better understand mechanism MPA. To ascertain presence any bias, two introduced models are employed: BIAS toolbox Generalized Signature Test. These examinations reveal notable MPA, towards center space. Also, possible future directions discussed. Our findings provide valuable insights into dynamics algorithm, fostering development new, unbiased, efficient algorithms.

Язык: Английский

Процитировано

6
A Novel Routing Protocol for UWSN Using Energy Efficient Marine Predator Optimization Technique DOI

Anmol Pandey,

Anujaya Singh,

Anushka Mishra

и другие.

Lecture notes in electrical engineering, Год журнала: 2025, Номер unknown, С. 333 - 344

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Evolutionary Cost Analysis and Computational Intelligence for Energy Efficiency in Internet of Things-Enabled Smart Cities: Multi-Sensor Data Fusion and Resilience to Link and Device Failures DOI Creative Commons
Khalid A. Darabkh,

Muna Al-Akhras

Smart Cities, Год журнала: 2025, Номер 8(2), С. 64 - 64

Опубликована: Апрель 9, 2025

This work presents an innovative, energy-efficient IoT routing protocol that combines advanced data fusion grouping and strategies to effectively tackle the challenges of management in smart cities. Our employs hierarchical Data Fusion Head (DFH), relay DFHs, marine predators algorithm, latter which is a reliable metaheuristic algorithm incorporates fitness function optimizes parameters such as how closely Sensor Nodes (SNs) group (DFG) are gathered together, distance sink node, proximity SNs within group, remaining energy (RE), Average Scale Building Occlusions (ASBO), Primary DFH (PDFH) rotation frequency. A key innovation our approach introduction techniques minimize redundant transmissions enhance quality DFG. By consolidating from multiple using algorithms, reduces volume transmitted information, leading significant savings. supports both direct routing, where fused flow straight multi-hop PDF chosen based on influential cost considers RE, ASBO. Given proposed efficient failure recovery strategies, redundancy management, techniques, it enhances overall system resilience, thereby ensuring high performance even unforeseen circumstances. Thorough simulations comparative analysis reveal protocol’s superior across metrics, namely, network lifespan, consumption, throughput, average delay. When compared most recent relevant protocols, including Particle Swarm Optimization-based clustering (PSO-EEC), linearly decreasing inertia weight PSO (LDIWPSO), Optimized Fuzzy Clustering Algorithm (OFCA), Novel PSO-based Protocol (NPSOP), achieves very promising results. Specifically, extends lifespan by 299% over PSO-EEC, 264% LDIWPSO, 306% OFCA, 249% NPSOP. It also consumption 254% relative 247% against 253% The throughput improvements reach 67% 59% 53% 50% fusing optimizing sets new benchmark for DFG, offering robust solution diverse deployments.

Язык: Английский

Процитировано

0
Enhancing Speaker Recognition Models with Noise-Resilient Feature Optimization Strategies DOI Creative Commons
Neha Chauhan, Tsuyoshi Isshiki, Dongju Li

и другие.

Acoustics, Год журнала: 2024, Номер 6(2), С. 439 - 469

Опубликована: Май 14, 2024

This paper delves into an in-depth exploration of speaker recognition methodologies, with a primary focus on three pivotal approaches: feature-level fusion, dimension reduction employing principal component analysis (PCA) and independent (ICA), feature optimization through genetic algorithm (GA) the marine predator (MPA). study conducts comprehensive experiments across diverse speech datasets characterized by varying noise levels counts. Impressively, research yields exceptional results different classifiers. For instance, TIMIT babble dataset (120 speakers), fusion achieves remarkable identification accuracy 92.7%, while various techniques combined K nearest neighbor (KNN) linear discriminant (LD) classifiers result in verification equal error rate (SV EER) 0.7%. Notably, this 93.5% SV EER 0.13% (630 speakers) using KNN classifier optimization. On white 630 accuracies 93.3% 83.5%, along values 0.58% 0.13%, respectively, were attained utilizing PCA (PCA-MPA) Furthermore, voxceleb1 dataset, PCA-MPA 95.2% 1.8%. These findings underscore significant enhancement computational speed performance facilitated strategies.

Язык: Английский

Процитировано

3