Evaluation of the prognostic significance and accuracy of screening tests for alcohol dependence based on the results of building a multilayer perceptron
M Sabugaa, B Senapati, Y Kupriyanov… - Computer Science On …, 2023 - Springer
The number of alcohol addicts is steadily increasing year by year all over the world.
Screening of abusers of alcoholic beverages in a timely manner will allow early diagnosis of …
Screening of abusers of alcoholic beverages in a timely manner will allow early diagnosis of …
Nuclear mass predictions using machine learning models
The exploration of nuclear mass or binding energy, a fundamental property of atomic nuclei,
remains at the forefront of nuclear physics research due to limitations in experimental …
remains at the forefront of nuclear physics research due to limitations in experimental …
[HTML][HTML] Development of a Machine Learning (ML)-Based Computational Model to Estimate the Engineering Properties of Portland Cement Concrete (PCC)
R Polo-Mendoza, G Martinez-Arguelles… - Arabian Journal for …, 2024 - Springer
Portland cement concrete (PCC) is the construction material most used worldwide. Hence,
its proper characterization is fundamental for the daily-basis engineering practice …
its proper characterization is fundamental for the daily-basis engineering practice …
[HTML][HTML] Designing a reliable machine learning system for accurately estimating the ultimate condition of FRP-confined concrete
Precisely forecasting how concrete reinforced with fiber-reinforced polymers (FRP) responds
under compression is essential for fine-tuning structural designs, ensuring constructions …
under compression is essential for fine-tuning structural designs, ensuring constructions …
Data-driven dryout prediction in helical-coiled once-through steam generator: A physics-informed approach leveraging the Buckingham Pi theorem
K Yang, H Liao, B Xu, Q Chen, Z Hou, H Wang - Energy, 2024 - Elsevier
A dimensionally consistent physics-informed neural network, named DimNet, has been
developed to predict dryout quality in helical coils. Central to its design is the automated and …
developed to predict dryout quality in helical coils. Central to its design is the automated and …
Nuclear binding energies in artificial neural networks
LX Zeng, YY Yin, XX Dong, LS Geng - Physical Review C, 2024 - APS
The binding energy or mass is one of the most fundamental properties of an atomic nucleus.
Precise binding energies are vital inputs for many nuclear physics and nuclear astrophysics …
Precise binding energies are vital inputs for many nuclear physics and nuclear astrophysics …
Predicting the masses of exotic hadrons with data augmentation using multilayer perceptron
H Bahtiyar - International Journal of Modern Physics A, 2023 - World Scientific
Recently, there have been significant developments in neural networks, which led to the
frequent use of neural networks in the physics literature. This work focuses on predicting the …
frequent use of neural networks in the physics literature. This work focuses on predicting the …
Perovskite Silicon Solar Cell Emulation using Multi-Layer Perceptron Deep Neural Network
Perovskite silicon solar cells have an unprecedentedly high-power conversion efficiency
compared to other solar cell technologies. This manuscript aims to accomplish two specific …
compared to other solar cell technologies. This manuscript aims to accomplish two specific …
Enhancing Multi-Layer Perceptron Performance with K-Means Clustering
Abstract Machine learning plays a crucial role in identifying patterns within data, with
classification being a prominent application. This study investigates the use of Multilayer …
classification being a prominent application. This study investigates the use of Multilayer …