A review on Machine learning aspect in physics and mechanics of glasses

J Singh, S Singh - Materials Science and Engineering: B, 2022 - Elsevier
The glass science and technology is a rapidly developing field which is focused on
development of new glasses with excellent properties. Glasses are the non-crystalline …

Artificial neural network training criterion formulation using error continuous domain

Z Hu, M Ivashchenko, L Lyushenko… - … Journal of Modern …, 2021 - search.proquest.com
One of the trends in information technologies is implementing neural networks in modern
software packages [1]. The fact that neural networks cannot be directly programmed (but …

[PDF][PDF] Classification and regression trees (CART) for predictive modeling in blended learning

NZ Zacharis - IJ Intelligent Systems and Applications, 2018 - mecs-press.org
Today, Internet and Web technologies not only provide students opportunities for flexible
interactivity with study materials, peers and instructors, but also generate large amounts of …

VEAD: Variance profile Exploitation for Anomaly Detection in real-time IoT data streaming

KNT Le, TB Dang, DT Le, SM Raza, M Kim, H Choo - Internet of Things, 2024 - Elsevier
The explosion of online streaming services in the Internet-of-Things (IoT) ecosystem poses
new difficulties in detecting anomalies in real-time and continuous data. The IoT data …

An efficient framework for obtaining the initial cluster centers

BK Mishra, SN Mohanty, RR Baidyanath, S Ali… - Scientific Reports, 2023 - nature.com
Clustering is an important tool for data mining since it can determine key patterns without
any prior supervisory information. The initial selection of cluster centers plays a key role in …

Design of digital economy consumer psychology prediction model based on canopy clustering algorithm

Y Zhang, P Ruan, J Zhao - Frontiers in Psychology, 2022 - frontiersin.org
With the continuous improvement of the level of science and technology, the popularization
of the Internet and the development of applications, online consumption has become a …

The application of spatial domain in optimum initialization for clustering image data using particle swarm optimization

M Dadjoo, SBF Nasrabadi - Expert Systems with Applications, 2021 - Elsevier
Clustering algorithms are affected by the initial seeds, therefore any improvement of the
initialization process can improve the final clustering results. There exist several initialization …

Accelerating energy-economic simulation models via machine learning-based emulation and time series aggregation

AJ Bogensperger, Y Fabel, J Ferstl - Energies, 2022 - mdpi.com
Energy-economic simulation models with high levels of detail, high time resolutions, or large
populations (eg, distribution networks, households, electric vehicles, energy communities) …

A performance of the scattered averaging technique based on the dataset for the cluster center initialization

ABW Putra, AFO Gaffar… - International Journal of …, 2021 - search.proquest.com
Clustering is one of the primary functions in data mining explorations and statistical data
analysis which widely used in various fields. There are two types of the clustering algorithms …

Analysis of China's Regional Economic Competitiveness, Regionalization, and Spatial Aggregation Characteristics Based on Density Clustering Algorithm

J He, R Liu - Mathematical Problems in Engineering, 2022 - Wiley Online Library
Regional development disparities, especially in developing countries, have traditionally
been one of the central issues of empirical research in regional economics. However, this …