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PAtbP-EnC: Identifying anti-tubercular peptides using multi-feature representation and genetic algorithm-based deep ensemble model
Mycobacterium tuberculosis, a highly perilous pathogen in humans, serves as the causative
agent of tuberculosis (TB), affecting nearly 33% of the global population. With the increasing …
agent of tuberculosis (TB), affecting nearly 33% of the global population. With the increasing …
[HTML][HTML] Evaluation of tree-based ensemble machine learning models in predicting stock price direction of movement
Forecasting the direction and trend of stock price is an important task which helps investors
to make prudent financial decisions in the stock market. Investment in the stock market has a …
to make prudent financial decisions in the stock market. Investment in the stock market has a …
Flash flood susceptibility modeling using new approaches of hybrid and ensemble tree-based machine learning algorithms
Flash flooding is considered one of the most dynamic natural disasters for which measures
need to be taken to minimize economic damages, adverse effects, and consequences by …
need to be taken to minimize economic damages, adverse effects, and consequences by …
Land cover classification from remote sensing images based on multi-scale fully convolutional network
ABSTRACT Although the Convolutional Neural Network (CNN) has shown great potential
for land cover classification, the frequently used single-scale convolution kernel limits the …
for land cover classification, the frequently used single-scale convolution kernel limits the …
Research on density grading of hybrid rice machine-transplanted blanket-seedlings based on multi-source unmanned aerial vehicle data and mechanized …
X Wang, Z Li, S Tan, H Li, L Qi, Y Wang, J Chen… - … and Electronics in …, 2024 - Elsevier
Due to the influence of seed conditions and environmental factors on growing process of
rice seedlings, there is a significant difference in the density of rice seedlings during …
rice seedlings, there is a significant difference in the density of rice seedlings during …
[PDF][PDF] An optimized extremely randomized tree model for breast cancer classification
Breast Cancer is a non-communicable disease seen primarily in women population. As per
the statistics published by the World Health Organization, it is presently ranked, globally, as …
the statistics published by the World Health Organization, it is presently ranked, globally, as …
Respiratory sound-base disease classification and characterization with deep/machine learning techniques
Respiratory diseases (RDs) are a leading cause of death globally, with over 490,000 deaths
in the EU and the US alone in 2017. Early detection of these diseases is crucial for …
in the EU and the US alone in 2017. Early detection of these diseases is crucial for …
Strip flatness prediction of cold rolling based on ensemble methods
W Yang, Z Zhao, L Zhu, X Gao, L Wang - Journal of Iron and Steel …, 2024 - Springer
Aiming at the problem of insufficient prediction accuracy of strip flatness at the outlet of cold
tandem rolling, the prediction performance of strip flatness based on different ensemble …
tandem rolling, the prediction performance of strip flatness based on different ensemble …
An integrated machine learning approach for evaluating critical success factors influencing project portfolio management adoption in the construction industry
MT Elnabwy, D Khalaf, EA Mlybari… - Engineering …, 2024 - emerald.com
Purpose In today's intricate and dynamic construction sector, traditional project management
techniques, which view projects in isolation, are no longer sufficient. Project Portfolio …
techniques, which view projects in isolation, are no longer sufficient. Project Portfolio …
Soil Organic Carbon Fractionation Assessment in Areas with High Fire Activity Using Diffuse Spectroscopy and Tree-Based Machine Learning Algorithms
Wildfires have a significant impact on Soil Organic Carbon (SOC) content and fractionation.
Here we used Diffuse Reflectance Spectroscopy (DRS) and Machine Learning (ML) …
Here we used Diffuse Reflectance Spectroscopy (DRS) and Machine Learning (ML) …