Search
Search Results
-
Anomaly detection of control rod drive mechanism using long short-term memory-based autoencoder and extreme gradient boosting
Anomaly detection for the control rod drive mechanism (CRDM) is key to enhancing the security of nuclear power plant equipment. In CRDM real-time...
-
Solar Flare Prediction and Feature Selection Using a Light-Gradient-Boosting Machine Algorithm
Solar flares are among the most severe space-weather phenomena, and they have the capacity to generate radiation storms and radio disruptions on...
-
Solar Flare Forecasting Using Time Series and Extreme Gradient Boosting Ensembles
Space weather events may cause damage to several types of technologies, including aviation, satellites, oil and gas industries, and electrical...
-
A Stacking-Based Ensemble Learning Method for Available Nitrogen Soil Prediction with a Handheld Micronear-Infrared Spectrometer
Soil-available nitrogen is a vital index related to the growth and development of crops. The real-time and nondestructive detection of the...
-
A Gradient Boosted Regression Tree Ensemble Model Using Wavelet Features for Post-acquisition Macromolecular Baseline Isolation from Brain MR Spectra
Broad macromolecular baseline (MMBL) is present throughout the magnetic resonance spectroscopy (MRS) spectrum of brain at short echo-time (TE)...
-
Ultra-Luminous X-Ray Sources: Extreme Accretion and Feedback
Ultra-luminous X-ray sources (ULXs) are the most extreme members of the X-ray binary population, exhibiting X-ray luminosities that can surpass the...
-
Optimization parameter prediction-based XGBoost of TF-QKD
Twin-field quantum key distribution (TF-QKD) can overcome the basic limits of QKD without repeaters. In practice, TF-QKD needs to optimize all...
-
Evaluation of Sample Preparation Methods for the Classification of Children’s Ca–Fe–Zn Oral Liquid by Libs
Different manufacturers do not produce the same quality of children’s Ca–Fe–Zn oral liquid due to different production materials and processes. To...
-
Size Optimization of Grid-Tied Hybrid Energy System by Employing Forecasted Meteorological Data
Embracing hybrid energy systems (HES) to ensure access to clean, reliable, and cost-effective energy is necessary for nations that are striving for...
-
Classification of Brandy and Cognac Production by Geographical Origin and Aging Using Raman Scattering and Machine Learning
The questions of develo** simple and accessible methods for monitoring the authenticity and quality of alcohol production based on Raman scattering...
-
Unveiling the Re, Cr, and I diffusion in saturated compacted bentonite using machine-learning methods
The safety assessment of high-level radioactive waste repositories requires a high predictive accuracy for radionuclide diffusion and a comprehensive...
-
Predicting the crystalline phase generation effectively in monosized granular matter using machine learning
AbstractWhen monosized granular matter is subjected to continuous mechanical disturbance, crystallization can be observed. The granular...
-
Acoustic resonances in non-Hermitian open systems
Acoustic resonances in open systems, which are usually associated with resonant modes characterized by complex eigenfrequencies, play a fundamental...
-
Unlocking Enhanced Rainfall Prediction: Leveraging Stacking Classifier Ensembles for Accurate Forecasting and Real-World Applications
Accurate prediction of rainfall is crucial for ensuring flight safety and various other applications. This study explores the use of Stacking...
-
Assessing the Predictability of Solar Energetic Particles with the Use of Machine Learning Techniques
A consistent approach for the inherently imbalanced problem of solar energetic particle (SEP) events binary prediction is being presented. This is...
-
Machine Learning Based Network Intrusion Detection System for Internet of Things Cybersecurity
The rapid expansion of the IoT devices and the vulnerability of the IoT systems are urging for investigating threats, improving existing security...
-
Analysis of the Effect of the St. Petersburg Megalopolis on Precipitation and Wind for Validation of Numerical Weather Forecasts
AbstractData on diurnal precipitation totals were retrieved by the gradient boosting method, as well as surface wind characteristics for St....
-
Boosted decision trees in the era of new physics: a smuon analysis case study
Machine learning algorithms are growing increasingly popular in particle physics analyses, where they are used for their ability to solve difficult...
-
Applying Machine Learning Algorithms to Predict Potential Energies and Atomic Forces during C-H Activation
Molecular dynamics (MD) simulations are useful in understanding the interaction between solid materials and molecules. However, performing MD...
-
Investigation of excellent transparent conducting electrode for efficient organometallic halide perovskite solar cell
As windows for the transmission of photons and electrons, applications of front contact transparent conducting electrodes (TCE) have played...
