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Fraud Detection in Mobile Payment Systems using an XGBoost-based Framework
Mobile payment systems are becoming more popular due to the increase in the number of smartphones, which, in turn, attracts the interest of...
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Forecasting gold price with the XGBoost algorithm and SHAP interaction values
Financial institutions, investors, mining companies and related firms need an effective accurate forecasting model to examine gold price fluctuations...
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Method for fusion of neighborhood rough set and XGBoost in welding process decision-making
Correct decision-making rules are essential to achieve the application of knowledge. The welding procedure document requires a rigorous knowledge...
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Predicting bank inactivity: A comparative analysis of machine learning techniques for imbalanced data
This study compares the predictive accuracy of a set of machine learning models coupled with three resampling techniques (Random Undersampling,...
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Forecasting carbon market volatility with big data
This paper proposes an ensemble forecasting model for carbon market volatility with structural factors and non-structural Baidu search index....
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Find who is doing social good: using machine learning to predict corporate social responsibility performance
Through a machine learning approach, this study develops a determinant model of corporate social responsibility (CSR) performance and comprehensively...
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Sales prediction hybrid models for retails using promotional pricing strategy as a key demand driver
The implementation of promotional pricing strategies constitutes a key component within the realm of retail revenue management. Nonetheless, the...
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A Comparative Study of Demand Forecasting Models for a Multi-Channel Retail Company: A Novel Hybrid Machine Learning Approach
Demand forecasting has been a major concern of operational strategy to manage the inventory and optimize the customer satisfaction level. The...
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Predicting daily hotel occupancy: a practical application for independent hotels
Accurately forecasting daily hotel occupancy is critical for revenue managers. Limited research focuses on predicting daily hotel occupancy by...
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How can entrepreneurs improve digital market segmentation? A comparative analysis of supervised and unsupervised learning algorithms
The identification of digital market segments to make value-creating propositions is a major challenge for entrepreneurs and marketing managers. New...
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Testing the Predictive Power of Machine Learning Algorithms for Stock Market Movements Based on Air Pollution Data
Air pollution has seriously threatened the lives of mankind. Governments throughout the world are taking several steps to reduce the impact of air...
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Precision in Building Extraction: Comparing Shallow and Deep Models Using LiDAR Data
Building segmentation is essential in infrastructure development, population management, and geological observations. This article targets shallow...
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From human business to machine learning—methods for automating real estate appraisals and their practical implications
Until recently, in most countries, the use of Automated Valuation Models (AVMs) in the lending process was only allowed for support purposes, and not...
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The role of political risk, uncertainty, and crude oil in predicting stock markets: evidence from the UAE economy
This study examines how the determinants of the political risk factor affect the forecasting performance of the United Arab Emirates’ stock market...
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Prediction of Airway Management of Trauma Patients Based on Machine Learning
Objective: To explore the application of different machine learning models to predict whether patients need endotracheal intubation, and to screen...
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Enabling active visitor management: local, short-term occupancy prediction at a touristic point of interest
After the temporary shock of the Covid-19 pandemic, the rapid recovery and resumed growth of the tourism sectors accelerates unsustainable tourism,...
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Predicting customer churn using machine learning: A case study in the software industry
Customer churn can be defined as the phenomenon of customers who discontinue their relationship with a company. This problem is transversal to many...
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COVID-19 vaccination performance of the U.S. states: a hybrid model of DEA and ensemble machine learning methods
Vaccination is seen as the most promising one among the efforts to stop COVID-19 and the U.S. government has given great importance to vaccination....
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Virtual metrology for chemical mechanical planarization of semiconductor wafers
Chemical mechanical planarization (CMP) is an important operation for surface modification of wafers in semiconductor manufacturing. Productivity and...
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Optimizing Offshore Wind Turbine Reliability and Costs Through Predictive Maintenance and SCADA Data Analysis
The Norwegian Ministry of Petroleum and Energy’s commissioned report signifies a significant step towards the government’s goal of designating...