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Jacobian Based Nonlinear Algorithms for Prediction of Optimized RF MEMS Switch Dimensions
This communication discusses the role of nonlinear algorithms in training the neural network, which predicts the optimized RF MEMS switch dimensions....
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Nonlinear Optimization Algorithms for Adjusting Selective Laser Melting Conditions
Abstract —The possibility and validity of using the mathematical algorithms of nonlinear optimization and machine learning to describe the dependence...
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Multi-Objective Optimization for Sustainable Machining of Hastelloy C-276 Using Evolutionary Algorithms
The use of petroleum-based lubricants in machining processes is dubious due to environmental hazards and risks to human health. Plant-based cutting...
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Performance Optimization of Ti-6Al-4V Milling Process Using Sustainable Cooling Approach and Application of Rao Algorithms
Titanium alloy is the most promising superalloy widely used in avionics systems, because of its high strength and great corrosion resistance....
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Machine Learning Algorithms in Photovoltaics: Evaluating Accuracy and Computational Cost Across Datasets of Different Generations, Sizes, and Complexities
This paper evaluates the compatibility of five different machine learning (ML) algorithms for analyzing datasets extracted from solar cell devices....
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Dimensional Error Minimization through Parameter Optimization for 3D Printed Nylon Aramid Composites Using SWARA-CoCoSo and Machine Learning Algorithms
FDM parts are susceptible to low-dimensional accuracy due to the involvement of numerous process parameters. It is highly essential to identify the...
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Using knowledge graphs and deep learning algorithms to enhance digital cultural heritage management
Cultural heritage management poses significant challenges for museums due to fragmented data, limited intelligent frameworks, and insufficient...
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Prediction model for corrosion rate of low-alloy steels under atmospheric conditions using machine learning algorithms
This work constructed a machine learning (ML) model to predict the atmospheric corrosion rate of low-alloy steels (LAS). The material properties of...
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Study on Equal Interval Sampling Method Promoting Efficiency of Post-Processing Algorithms for Infrared Thermography Inspecting Carbon-Fiber Reinforced Plastics Composites
AbstractThe broadening use of carbon-fiber reinforced plastics (CFRP) in various industries has raised safety concerns. To control the hazard,...
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QoS-aware resource allocation method for the internet of things using triplet and heterogeneous earliest finish time algorithms
Recently, the Internet of Things (IoT) has attracted researchers’ and industries’ attention for changing the way humans live and granting them unique...
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Predicting Forced Blower Failures Using Machine Learning Algorithms and Vibration Data for Effective Maintenance Strategies
The emergence of Industry 4.0, also known as the fourth industrial revolution, has brought forth the concept of prognostics and health management...
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Modeling and optimization of nanovector drug delivery systems: exploring the most efficient algorithms
The most efficient artificial intelligence (AI) and metaheuristic algorithms have been assessed for the design of nanovector (NV) drug delivery...
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Prediction of Efficiency for KSnI3 Perovskite Solar Cells Using Supervised Machine Learning Algorithms
Machine learning possesses enormous capability for accelerating materials research. A dataset of 40,845 data points, each containing 52 features for...
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Path Planning Algorithms of the Mobile Robots Control
The purpose of this paper is to provide a complete analysis and comparison of the most used algorithms to plan the trajectories of mobile robots. By...
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Predicting Stress–Strain Characteristics of Hot Deformed Cu-Zr Metallic Glass Alloy Composite Nanowires Using Supervised Machine Learning Algorithms
In this paper, classical molecular dynamics simulations of tensile deformation on Cu 50 Zr 50 metallic glass alloy composite nanowires have been carried...
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Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows
The automation of ab initio simulations is essential in view of performing high-throughput (HT) computational screenings oriented to the discovery of...
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Evaluating data-driven algorithms for predicting mechanical properties with small datasets: A case study on gear steel hardenability
Data-driven algorithms for predicting mechanical properties with small datasets are evaluated in a case study on gear steel hardenability. The...
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Development of Image Reconstruction Algorithms for Few-View Computed Tomography at RFNC–VNIITF: History, State of the Art, and Prospects
AbstractIn the last 20 yr, RFNC–VNIITF has developed a linear-induction-accelerator-based radiography complex capable of reconstructing the 3D inner...
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Artificial Intelligence and Machine Learning in Metallurgy. Part 1. Methods and Algorithms
The article contains information about machine learning methods used in modern metallurgy. The description of machine learning methods and their role...
