Academic Articles & Research Papers

ExNCDIA: an explainable ensemble learning framework for predicting non-chemotherapy drug-induced agranulocytosis and interpreting structural associations.

Predicting the Current Potential Suitable Habitat of Pinus tabuliformis in China Using Multi-Source Environmental Data and Ensemble Learning Models.

Calibrated, cost-sensitive, explainable ensemble learning for customer churn prediction in retail banking: a leakage-safe pipeline and single-dataset case study.

Measuring Neighborhood Socioeconomic Status from Sky and Street: An Ensemble Learning Framework.

Hybrid heterogeneous ensemble learning framework for flood susceptibility mapping in Balochistan, Pakistan

Study region: The National Highways 85 and 50, key routes of the China–Pakistan Economic Corridor (CPEC) in Balochistan, Pakistan. Study focus: Flooding is a natural disaster that is becoming increasingly frequent and severe. The National H...

Power Load Probabilistic Prediction Based on Multi-Value Quantile Regression and Timing Fusion Ensemble Learning Model

The core component to ensure the refined and safe operation of distribution network scheduling is 10 kV bus load probabilistic prediction. However, existing probabilistic prediction methods suffer from insufficient dynamic feature extractio...

Day-Ahead Electric Load Forecasting for the Residential Building with a Small-Size Dataset Based on a Self-Organizing Map and a Stacking Ensemble Learning Method

Electric load forecasting for buildings is important as it assists building managers or system operators to plan energy usage and strategize accordingly. Recent increases in the adoption of advanced metering infrastructure (AMI) have made b...

Analyzing Sentiments in eLearning: A Comparative Study of Bangla and Romanized Bangla Text Using Transformers

In the modern world, learning is becoming increasingly critical due to rapid technological breakthroughs, which highlight the need for continuous skill development in both the personal and professional spheres. As a result, eLearning is a c...

A Novel Methodology for Human Kinematics Motion Detection Based on Smartphones Sensor Data Using Artificial Intelligence

Kinematic motion detection aims to determine a person’s actions based on activity data. Human kinematic motion detection has many valuable applications in health care, such as health monitoring, preventing obesity, virtual reality, daily li...

A comprehensive review on ensemble deep learning: Opportunities and challenges

In machine learning, two approaches outperform traditional algorithms: ensemble learning and deep learning. The former refers to methods that integrate multiple base models in the same framework to obtain a stronger model that outperforms t...

A Deep Ensemble Learning Method for Effort-Aware Just-In-Time Defect Prediction

Since the introduction of just-in-time effort aware defect prediction, many researchers are focusing on evaluating the different learning methods, which can predict the defect inducing changes in a software product. In order to predict thes...

Stacking Ensemble Approach for Churn Prediction: Integrating CNN and Machine Learning Models with CatBoost Meta-Learner

In the telecom industry, predicting customer churn is crucial for improving customer retention. In literature, the use of single classifiers is predominantly focused. Customer data is complex data due to class imbalance and contain multiple...

Synergistic multi-altimeter for estimating water level in the coastal zone of Beibu Gulf using SEL, ALES + and BFAST algorithms

Accurately monitoring and predicting the large-scale dynamic changes of water levels in coastal zones is essential for its protection, restoration and sustainable development. However, there has been a challenge for achieving this goal usin...

Lightweight Ensemble Learning based on Post-Hoc Probability Fusion with Its Application to Lung CT Image Classification.