Incorporating sparse model machine learning in designing cultural heritage landscapes
Managing, protecting, and the evolutionary development of historical landscapes require
robust frameworks and processes for forming datasets and advanced decision support tools …
robust frameworks and processes for forming datasets and advanced decision support tools …
Remaining useful life prediction of bearings under different working conditions using a deep feature disentanglement based transfer learning method
T Hu, Y Guo, L Gu, Y Zhou, Z Zhang, Z Zhou - Reliability Engineering & …, 2022 - Elsevier
The data distribution discrepancy between the training and test samples makes it
challenging for the remaining useful life (RUL) prediction under different working conditions …
challenging for the remaining useful life (RUL) prediction under different working conditions …
Local linear embedding with adaptive neighbors
Dimensionality reduction is one of the most important techniques in the field of data mining.
It embeds high-dimensional data into a low-dimensional vector space while keeping the …
It embeds high-dimensional data into a low-dimensional vector space while keeping the …
Selection of contributing factors for predicting landslide susceptibility using machine learning and deep learning models
Landslides are a common natural disaster that can cause casualties, property safety threats
and economic losses. Therefore, it is important to understand or predict the probability of …
and economic losses. Therefore, it is important to understand or predict the probability of …
A new approach for remaining useful life prediction of bearings using 1D-ternary patterns with LSTM
E Akcan, Y Kaya - Journal of the Brazilian Society of Mechanical Sciences …, 2023 - Springer
Bearings frequently experience malfunctions in mechanical systems, directly impacting
system performance. Accurate prediction of bearing failures is crucial for maintenance …
system performance. Accurate prediction of bearing failures is crucial for maintenance …
Multi-layer adaptive spatial-temporal feature fusion network for efficient food image recognition
S Phiphitphatphaisit, O Surinta - Expert Systems with Applications, 2024 - Elsevier
Numerous deep learning methods have been developed to tackle the challenges of
recognizing food images, including convolutional neural networks, deep feature extraction …
recognizing food images, including convolutional neural networks, deep feature extraction …
A novel trading system for the stock market using Deep Q-Network action and instance selection
M Park, J Kim, D Enke - Expert Systems with Applications, 2024 - Elsevier
Stock trading is a complex decision-making process that involves predicting market price
movements. Many investors attempt to buy at low prices and sell at high prices, which can …
movements. Many investors attempt to buy at low prices and sell at high prices, which can …
Seleksi Fitur pada Supervised Learning: Klasifikasi Prestasi Belajar Mahasiswa Saat dan Pasca Pandemi COVID-19
A Rahmadeyan, M Mustakim - Jurnal Nasional Teknologi dan …, 2023 - teknosi.fti.unand.ac.id
Dampak pandemi COVID-19 membuat lembaga pendidikan mengubah metode belajar
menjadi pembelajaran jarak jauh secara daring. Banyak perguruan tinggi menyatakan …
menjadi pembelajaran jarak jauh secara daring. Banyak perguruan tinggi menyatakan …
Causality-based PCA Methods for Condition Modeling of Mechatronic Systems
J Liu, Y Xu, Y Chen - IEEE Transactions on Industrial …, 2023 - ieeexplore.ieee.org
This article investigates the feature dimensionality reduction problem of high-dimensional
data in condition modeling of complex mechatronic systems, aiming at improving …
data in condition modeling of complex mechatronic systems, aiming at improving …
The relative importance of ESG pillars: A two‐step machine learning and analytical framework
This study aims to contribute to the ongoing and inconclusive debates regarding the relative
significance of environmental, social, and governance (ESG) sustainability key performance …
significance of environmental, social, and governance (ESG) sustainability key performance …