Ensemble multifeatured deep learning models and applications: A survey
Ensemble multifeatured deep learning methodology has emerged as a powerful approach
to overcome the limitations of single deep learning models in terms of generalization …
to overcome the limitations of single deep learning models in terms of generalization …
A Novel WD-SARIMAX model for temperature forecasting using daily delhi climate dataset
Forecasting is defined as the process of estimating the change in uncertain situations. One
of the most vital aspects of many applications is temperature forecasting. Using the Daily …
of the most vital aspects of many applications is temperature forecasting. Using the Daily …
Study on the influence of built-in open-hole dust cleaner on the cleaning performance of cartridge filter
S Li, H Cheng, S Hu, G Wen, A Zhou, C Gui… - Process Safety and …, 2023 - Elsevier
Pleated cartridge dust collectors are widely used in various industrial production
environments, in its use, pulse-jet cleaning is a crucial step. Despite the importance of pulse …
environments, in its use, pulse-jet cleaning is a crucial step. Despite the importance of pulse …
Comparison of Feature Selection and Supervised Methods for Classifying Gait Disorders
M Shayestegan, J Kohout, L Verešpejová… - IEEE …, 2024 - ieeexplore.ieee.org
Recently, systems for classifying gait disorders have been of great interest. However,
quantifying the progress of these disorders has been highly dependent on a physician's …
quantifying the progress of these disorders has been highly dependent on a physician's …
Future challenges of particulate matters (PMs) monitoring by computing associations among extracted multimodal features applying Bayesian network approach
The particulate matter (PM) is emitted from diverse sources and affects the human health
very badly. In the past, researchers applied different automated computational tools in the …
very badly. In the past, researchers applied different automated computational tools in the …
A multi-MLP prediction for inventory management in manufacturing execution system
Artificial intelligence (AI) positively remodels industrial processes, notably inventory
management (IM), from planning, scheduling, and optimization to logistics. Intelligent …
management (IM), from planning, scheduling, and optimization to logistics. Intelligent …
Proposed methodology for gait recognition using generative adversarial network with different feature selectors
Today, investigating gait recognition as a biometric technology has become necessary,
especially after the COVID-19 pandemic broke out in the world. This paper proposes a deep …
especially after the COVID-19 pandemic broke out in the world. This paper proposes a deep …
Comparative study of AutoML approach, conventional ensemble learning method, and KNearest Oracle-AutoML model for predicting student dropouts in Sub-Saharan …
Student dropout in secondary schools is a major issue in developing countries, particularly
in Sub-Saharan Africa. Sub-Saharan African countries had the highest dropout rate (37.5%) …
in Sub-Saharan Africa. Sub-Saharan African countries had the highest dropout rate (37.5%) …
A robust supervised machine learning based approach for offline-online traffic classification of software-defined networking
Due to the exponential increase of internet applications and network users, network traffic
classification (NTC) is a crucial study subject. It successfully improves network service …
classification (NTC) is a crucial study subject. It successfully improves network service …
An integrated Two-Layered Voting (TLV) framework for coronary artery disease prediction using machine learning classifiers
Cardiovascular problems have emerged as a significant concern, adversely impacting
individuals across all age groups. Several recent research studies have used Machine …
individuals across all age groups. Several recent research studies have used Machine …