80 results match your criteria: "Archives Of Computational Methods In Engineering[Journal]"

This scoping review assesses the current use of simulation-based design optimization (SBDO) in marine engineering, focusing on identifying research trends, methodologies, and application areas. Analyzing 277 studies from Scopus and Web of Science, the review finds that SBDO is predominantly applied to optimizing marine vessel hulls, including both surface and underwater types, and extends to key components like bows, sterns, propellers, and fins. It also covers marine structures and renewable energy systems.

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Artificial Intelligence in Physical Sciences: Symbolic Regression Trends and Perspectives.

Arch Comput Methods Eng

April 2023

Condensed Matter Physics Laboratory, Department of Physics, University of Thessaly, Lamia, 35100 Greece.

Unlabelled: Symbolic regression (SR) is a machine learning-based regression method based on genetic programming principles that integrates techniques and processes from heterogeneous scientific fields and is capable of providing analytical equations purely from data. This remarkable characteristic diminishes the need to incorporate prior knowledge about the investigated system. SR can spot profound and elucidate ambiguous relations that can be generalizable, applicable, explainable and span over most scientific, technological, economical, and social principles.

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Viruses have killed and infected millions of people across the world. It causes several chronic diseases like COVID-19, HIV, and hepatitis. To cope with such diseases and virus infections, antiviral peptides (AVPs) have been applied in the design of drugs.

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Artificial intelligence is the most powerful and promising tool for the present analytic technologies. It can provide real-time insights into disease spread and predict new pandemic epicenters by processing massive amount of data. The main aim of the paper is to detect and classify multiple infectious diseases using deep learning models.

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A Structured Analysis to study the Role of Machine Learning and Deep Learning in The Healthcare Sector with Big Data Analytics.

Arch Comput Methods Eng

March 2023

Center of Excellence in Weather & Climate Analytics, Atmospheric Sciences Research Center (ASRC), University at Albany (UAlbany), State University of New York (SUNY), Albany, New York 12226 USA.

Machine and deep learning are used worldwide. Machine Learning (ML) and Deep Learning (DL) are playing an increasingly important role in the healthcare sector, particularly when combined with big data analytics. Some of the ways that ML and DL are being used in healthcare include Predictive Analytics, Medical Image Analysis, Drug Discovery, Personalized Medicine, and Electronic Health Records (EHR) Analysis.

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Recent Developments in Equilibrium Optimizer Algorithm: Its Variants and Applications.

Arch Comput Methods Eng

April 2023

Department of Computer Science and Application, Midnapore College (Autonomous), Paschim Medinipur, Midnapore, West Bengal India.

There have been many algorithms created and introduced in the literature inspired by various events observable in nature, such as evolutionary phenomena, the actions of social creatures or agents, broad principles based on physical processes, the nature of chemical reactions, human behavior, superiority, and intelligence, intelligent behavior of plants, numerical techniques and mathematics programming procedure and its orientation. Nature-inspired metaheuristic algorithms have dominated the scientific literature and have become a widely used computing paradigm over the past two decades. Equilibrium Optimizer, popularly known as EO, is a population-based, nature-inspired meta-heuristics that belongs to the class of Physics based optimization algorithms, enthused by dynamic source and sink models with a physics foundation that are used to make educated guesses about equilibrium states.

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A Comprehensive Survey on Aquila Optimizer.

Arch Comput Methods Eng

June 2023

Department of Computer Science and Application, Midnapore College (Autonomous), Paschim Medinipur, West Bengal India.

Aquila Optimizer (AO) is a well-known nature-inspired optimization algorithm (NIOA) that was created in 2021 based on the prey grabbing behavior of Aquila. AO is a population-based NIOA that has demonstrated its effectiveness in the field of complex and nonlinear optimization in a short period of time. As a result, the purpose of this study is to provide an updated survey on the topic.

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The machine learning (ML) paradigm has gained much popularity today. Its algorithmic models are employed in every field, such as natural language processing, pattern recognition, object detection, image recognition, earth observation and many other research areas. In fact, machine learning technologies and their inevitable impact suffice in many technological transformation agendas currently being propagated by many nations, for which the already yielded benefits are outstanding.

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Despite the simplicity of the whale optimization algorithm (WOA) and its success in solving some optimization problems, it faces many issues. Thus, WOA has attracted scholars' attention, and researchers frequently prefer to employ and improve it to address real-world application optimization problems. As a result, many WOA variations have been developed, usually using two main approaches improvement and hybridization.

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Marine Predators Algorithm: A Review.

Arch Comput Methods Eng

April 2023

Center for Artificial Intelligence Research and Optimization, Torrens University, Adelaide, Australia.

Marine Predators Algorithm (MPA) is a recent nature-inspired optimizer stemmed from widespread foraging mechanisms based on Lévy and Brownian movements in ocean predators. Due to its superb features, such as derivative-free, parameter-less, easy-to-use, flexible, and simplicity, MPA is quickly evolved for a wide range of optimization problems in a short period. Therefore, its impressive characteristics inspire this review to analyze and discuss the primary MPA research studies established.

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On the Analyses of Medical Images Using Traditional Machine Learning Techniques and Convolutional Neural Networks.

Arch Comput Methods Eng

April 2023

Artificial Intelligence and Data Analytics (AIDA) Lab, College of Computer & Information Sciences (CCIS), Prince Sultan University, Riyadh, 11586 Kingdom of Saudi Arabia.

Convolutional neural network (CNN) has shown dissuasive accomplishment on different areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information Retrieval, Medical Image Registration, Multi-lingual translation, Local language Processing, Anomaly Detection on video and Speech Recognition. CNN is a special type of Neural Network, which has compelling and effective learning ability to learn features at several steps during augmentation of the data. Recently, different interesting and inspiring ideas of Deep Learning (DL) such as different activation functions, hyperparameter optimization, regularization, momentum and loss functions has improved the performance, operation and execution of CNN Different internal architecture innovation of CNN and different representational style of CNN has significantly improved the performance.

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A Comprehensive Survey on Arithmetic Optimization Algorithm.

Arch Comput Methods Eng

March 2023

Department of Computer Applications, Sikkim University, Gangtok, Sikkim India.

Arithmetic Optimization Algorithm (AOA) is a recently developed population-based nature-inspired optimization algorithm (NIOA). AOA is designed under the inspiration of the distribution behavior of the main arithmetic operators in mathematics and hence, it also belongs to mathematics-inspired optimization algorithm (MIOA). MIOA is a powerful subset of NIOA and AOA is a proficient member of it.

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An Inclusive Survey on Marine Predators Algorithm: Variants and Applications.

Arch Comput Methods Eng

February 2023

Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, Kolkata, West Bengal India.

Marine Predators Algorithm (MPA) is the existing population-based meta-heuristic algorithms that falls under the category of Nature-Inspired Optimization Algorithm (NIOA) enthused by the foraging actions of the marine predators that principally pursues Levy or Brownian approach as its foraging strategy. Furthermore, it employs the optimal encounter rate stratagem involving both the predator as well as prey. Since its introduction by Faramarzi in the year 2020, MPA has gained enormous popularity and has been employed in numerous application areas ranging from Mathematical and Engineering Optimization problems to Fog Computing to Image Processing to Photovoltaic System to Wind-Solar Generation System for resolving continuous optimization problems.

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Recent Versions and Applications of Sparrow Search Algorithm.

Arch Comput Methods Eng

February 2023

Artificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman, United Arab Emirates.

This paper reviews the latest versions and applications of sparrow search algorithm (SSA). It is a recent swarm-based algorithm proposed in 2020 rapidly grew due to its simple and optimistic features. SSA is inspired by the sparrow living style of foraging and the anti-predation behavior of sparrows.

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Self-supervised Learning: A Succinct Review.

Arch Comput Methods Eng

January 2023

University Institute of Engineering and Technology, Panjab University, Chandigarh, India.

Machine learning has made significant advances in the field of image processing. The foundation of this success is supervised learning, which necessitates annotated labels generated by humans and hence learns from labelled data, whereas unsupervised learning learns from unlabeled data. Self-supervised learning (SSL) is a type of un-supervised learning that helps in the performance of downstream computer vision tasks such as object detection, image comprehension, image segmentation, and so on.

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Image-Based Simulation (IBSim) is the process by which a digital representation of a real geometry is generated from image data for the purpose of performing a simulation with greater accuracy than with idealised Computer Aided Design (CAD) based simulations. Whilst IBSim originates in the biomedical field, the wider adoption of imaging for non-destructive testing and evaluation (NDT/NDE) within the High-Value Manufacturing (HVM) sector has allowed wider use of IBSim in recent years. IBSim is invaluable in scenarios where there exists a non-negligible variation between the 'as designed' and 'as manufactured' state of parts.

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Meta-heuristic algorithms have a high position among academic researchers in various fields, such as science and engineering, in solving optimization problems. These algorithms can provide the most optimal solutions for optimization problems. This paper investigates a new meta-heuristic algorithm called Slime Mould algorithm (SMA) from different optimization aspects.

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COVID-19-The Role of Artificial Intelligence, Machine Learning, and Deep Learning: A Newfangled.

Arch Comput Methods Eng

January 2023

Sathyabama Centre for Advanced Studies, Sathyabama Institute of Science and Technology, Rajiv Gandhi Salai, Chennai, Tamil Nadu 600119 India.

The absolute previously infected novel coronavirus (COVID-19) was found in Wuhan, China, in December 2019. The COVID-19 epidemic has spread to more than 220 nations and territories globally and has altogether influenced each part of our day-to-day lives. As of 9th March 2022, a total aggregate of 44,78,82,185 (60,07,317) contaminated (dead) COVID-19 cases were accounted for all over the world.

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Archimedes Optimizer: Theory, Analysis, Improvements, and Applications.

Arch Comput Methods Eng

January 2023

Department of Computer Science and Application, Midnapore College (Autonomous), Paschim Medinipur, Midnapore, West Bengal India.

The intricacy of the real-world numerical optimization tribulations has full-fledged and diversely amplified necessitating proficient yet ingenious optimization algorithms. In the domain wherein the classical approaches fall short, the predicament resolving nature-inspired optimization algorithms (NIOA) tend to hit upon an excellent solution to unbendable optimization problems consuming sensible computation time. Nevertheless, in the last few years approaches anchored in nonlinear physics have been anticipated, announced, and flourished.

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Mental Health Analysis in Social Media Posts: A Survey.

Arch Comput Methods Eng

January 2023

University of Florida, Gainesville, FL 32601 USA.

The surge in internet use to express personal thoughts and beliefs makes it increasingly feasible for the social NLP research community to find and validate associations between and . Cross-sectional and longitudinal studies of social media data bring to fore the importance of real-time responsible AI models for mental health analysis. Aiming to classify the research directions for social computing and tracking advances in the development of machine learning (ML) and deep learning (DL) based models, we propose a comprehensive survey on .

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Gradient-Based Optimizer (GBO): A Review, Theory, Variants, and Applications.

Arch Comput Methods Eng

December 2022

The Custodian of the Two Holy Mosques Institute for Hajj and Umrah Research, Umm Al-Qura University, Mecca, Saudi Arabia.

This paper introduces a comprehensive survey of a new population-based algorithm so-called gradient-based optimizer (GBO) and analyzes its major features. GBO considers as one of the most effective optimization algorithm where it was utilized in different problems and domains, successfully. This review introduces set of related works of GBO where distributed into; GBO variants, GBO applications, and evaluate the efficiency of GBO compared with other metaheuristic algorithms.

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In the developing world, parasites are responsible for causing several serious health problems, with relatively high infections in human beings. The traditional manual light microscopy process of parasite recognition remains the golden standard approach for the diagnosis of parasitic species, but this approach is time-consuming, highly tedious, and also difficult to maintain consistency but essential in parasitological classification for carrying out several experimental observations. Therefore, it is meaningful to apply deep learning to address these challenges.

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Cloud Computing has emerged as a computing paradigm where services are provided through the internet in recent years. Offering on-demand services has transformed the IT companies' working environment, leading to a linearly increasing trend of its usage. The provisioning of the Computing infrastructure is achieved with the help of virtual machines.

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There is a need for some techniques to solve various problems in today's computing world. Metaheuristic algorithms are one of the techniques which are capable of providing practical solutions to such issues. Due to their efficiency, metaheuristic algorithms are now used in healthcare data to diagnose diseases practically and with better results than traditional methods.

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Mathematical Foundations of Adaptive Isogeometric Analysis.

Arch Comput Methods Eng

September 2022

École polytechnique fédérale de Lausanne, Institute of Mathematics, 1015 Lausanne, Switzerland.

This paper reviews the state of the art and discusses recent developments in the field of adaptive isogeometric analysis, with special focus on the mathematical theory. This includes an overview of available spline technologies for the local resolution of possible singularities as well as the state-of-the-art formulation of convergence and quasi-optimality of adaptive algorithms for both the finite element method and the boundary element method in the frame of isogeometric analysis.

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