Results 61 to 70 of about 87,787 (275)
Blood Coagulation Algorithm: A Novel Bio-Inspired Meta-Heuristic Algorithm for Global Optimization
This paper introduces a novel population-based bio-inspired meta-heuristic optimization algorithm, called Blood Coagulation Algorithm (BCA). BCA derives inspiration from the process of blood coagulation in the human body.
Drishti Yadav
doaj +1 more source
Satellite downlink scheduling problem: A case study [PDF]
The synthetic aperture radar (SAR) technology enables satellites to efficiently acquire high quality images of the Earth surface. This generates significant communication traffic from the satellite to the ground stations, and, thus, image downlinking ...
Abraham P. Punnen +34 more
core +2 more sources
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +4 more
wiley +1 more source
Abstract Everything can be connected in the Internet of Things (IoTs) technology that enables efficient communication between connected objects. IoTs industry‐based meta‐heuristic and mining algorithms, which are considered an important field of Artificial Intelligence will be used to construct a healthcare application in this study for lowering costs,
Muhaned Al‐Hashimi +4 more
wiley +1 more source
A Hybrid Meta-Heuristic Algorithm based on Imperialist Competition Algorithm
The human has always been to find the best in all things. This Perfectionism has led to the creation of optimization methods. The goal of optimization is to determine the variables and find the best acceptable answer Due to the limitations of the problem, So that the objective function is minimum or maximum.
Roustaei, R., Yousefi Fakhr, F.
openaire +2 more sources
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
We utilise a metaheuristic optimisation method, inspired by nature, called the Lévy‐flight firefly algorithm (LFA), to tackle the power regulation and user grouping in the NOMA systems. Abstract The non‐orthogonal multiple access strategies have shown promise to boost fifth generation and sixth generation wireless networks' spectral efficiency and ...
Zaid Albataineh +4 more
wiley +1 more source
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
The synergy between deep learning and meta-heuristic algorithms presents a promising avenue for tackling the complexities of energy-related modeling and forecasting tasks.
Eghbal Hosseini +7 more
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Meta-heuristic algorithm has been a research hotspot in solving the optimal solution of large-scale functions. However, meta-heuristic algorithms are prone to fall into local optimum problems, such as the recently proposed dolphin swarm algorithm (DSA ...
Weibiao Qiao, Zhe Yang
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