A new artificial intelligence strategy for predicting the groundwater level over the Rafsanjan aquifer in Iran
This study presents a new strategy to predict the monthly groundwater level with short-and
long-lead times over the Rafsanjan aquifer in Iran using an ensemble machine learning …
long-lead times over the Rafsanjan aquifer in Iran using an ensemble machine learning …
Cascading logistic regression onto gradient boosted decision trees for forecasting and trading stock indices
F Zhou, Q Zhang, D Sornette, L Jiang - Applied Soft Computing, 2019 - Elsevier
Forecasting the direction of the daily changes of stock indices is an important yet difficult task
for market participants. Advances on data mining and machine learning make it possible to …
for market participants. Advances on data mining and machine learning make it possible to …
Ensemble deep learning-based fault diagnosis of rotor bearing systems
S Ma, F Chu - Computers in industry, 2019 - Elsevier
For rotating machinery, early and accurate diagnosis of rotor and bearing component fault is
of great significance. The classic fault diagnosis model includes two key modules, feature …
of great significance. The classic fault diagnosis model includes two key modules, feature …
Metaheuristic-based ensemble learning: an extensive review of methods and applications
Ensemble learning has become a cornerstone in various classification and regression tasks,
leveraging its robust learning capacity across disciplines. However, the computational time …
leveraging its robust learning capacity across disciplines. However, the computational time …
A multiobjective evolutionary nonlinear ensemble learning with evolutionary feature selection for silicon prediction in blast furnace
In the blast furnace ironmaking process, accurate prediction of silicon content in molten iron
is of great significance for maintaining stable furnace conditions, improving hot metal quality …
is of great significance for maintaining stable furnace conditions, improving hot metal quality …
Loan default prediction using a credit rating-specific and multi-objective ensemble learning scheme
For the consumer lending industry, credit risk assessment is a crucial task for evaluating the
default probability of loan applications given the potential loss caused by default. In …
default probability of loan applications given the potential loss caused by default. In …
Ensemble learning by means of a multi-objective optimization design approach for dealing with imbalanced data sets
Ensemble learning methods have already shown to be powerful techniques for creating
classifiers. However, when dealing with real-world engineering problems, class imbalance …
classifiers. However, when dealing with real-world engineering problems, class imbalance …
Application of newly developed ensemble machine learning models for daily suspended sediment load prediction and related uncertainty analysis
A Sharafati, SB Haji Seyed Asadollah… - Hydrological …, 2020 - Taylor & Francis
Ensemble machine learning models have been widely used in hydro-systems modeling as
robust prediction tools that combine multiple decision trees. In this study, three newly …
robust prediction tools that combine multiple decision trees. In this study, three newly …
An improved ensemble pruning for mammogram classification using modified Bees algorithm
Ensemble learning has piqued the curiosity of the machine learning applications. It recently
drawn serious attention in computer-aided diagnostic system (CADs) due to their potential to …
drawn serious attention in computer-aided diagnostic system (CADs) due to their potential to …
Superpixel-based multiobjective change detection based on self-adaptive neighborhood-based binary differential evolution
With strong penetrability and high resolution, synthetic aperture radar (SAR) images have
been widely used in remote sensing image change detection. With the essence of heuristics …
been widely used in remote sensing image change detection. With the essence of heuristics …