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ISSN: 2666-7649
CN: 61-1530/TN
p-ISSN: 2097-3187

A machine learning approach to formation of earthquake categories using hierarchies of magnitude and consequence to guide emergency management

This study deployed k-means clustering to formulate earthquake categories based on magnitude and consequence, using global earthquake data spanning from 1900 to 2021. Based on patterns within the historical...

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Revolutionizing spatial data analysis: unveiling a cutting-edge approach for batch coordinate transformation

Spatial data have become indispensable across various disciplines and provide crucial insights. These data are associated with coordinates and different coordinate systems. However, the diversity of...

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Effects of economic factors on median list and selling prices in the U.S. housing market

This study investigates the effects of key economic factors on the median list price and median selling price in the U.S. housing market. Key economic factors such as interest rates, unemployment rates,...

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Dual-stage ensemble approach using online knowledge distillation for forecasting carbon emissions in the electric power industry

The electric power industry is the key to achieving the goals of carbon peak and neutrality. Accurate forecasting of carbon emissions in the electric power industry can aid in the prompt adjustment...

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Understanding the antecedents of patients’ missed appointments: The perspective of attribution theory

The occurrence of missed appointment appointments from online outpatient bookings significantly hinders the operational efficiency of outpatient services. This study aimed to investigate various factors...

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Forecasting stock closing prices with an application to airline company data

Forecasting stock market movements is a challenging task from the practitioners’ point of view. We explore how model selection via the least absolute shrinkage and selection operator (LASSO) approach...

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Data- and management-driven metaverse research

The metaverse has become a very important phenomenon in society because of the emergence of new technologies. The widespread adoption of the metaverse has generated significant discussions about the...

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Using multi-criteria decision-making and machine learning for football player selection and performance prediction: A systematic review

Evaluating and selecting players to suit football clubs and decision-makers (coaches, managers, technical, and medical staff) is a difficult process from a managerial-financial and sporting perspective....

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Hybrid scientific article recommendation system with COOT optimization

Today, recommendation systems are everywhere, making a variety of activities considerably more manageable. These systems help users by personalizing their suggestions to their interests and needs. They...

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Anomalous node detection in attributed social networks using dual variational autoencoder with generative adversarial networks

Many types of real-world information systems, including social media and e-commerce platforms, can be modelled by means of attribute-rich, connected networks. The goal of anomaly detection in artificial...

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Virtual manufacturing in industry 4.0: A review

Virtual manufacturing is one of the key components of Industry 4.0, the fourth industrial revolution, in improving manufacturing processes. Virtual manufacturing enables manufacturers to optimize their...

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The dynamics of price discovery between US and Chinese soybean market: A wavelet approach to understanding the effects of Sino-U.S. trade conflict and COVID-19 pandemic

During geopolitical crises, the price stability of agricultural commodities is critical for national security. Understanding the dynamics of pricing power between the United States and China and how...

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Using machine learning to identify primary features in choosing electric vehicles based on income levels

An electric vehicle is becoming one of the popular choices when choosing a vehicle. People are generally impressed with electric vehicles’ zero-emission and smooth drives, while unstable battery duration...

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Hybrid distributed feature selection using PSO-MI

Feature Selection (FS) is a data preprocessing step in Machine Learning (ML) that selects a subset of relevant and informative features from a large feature pool. FS helps ML models improve their predictive...

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Audiovisual speech recognition based on a deep convolutional neural network

Audiovisual speech recognition is an emerging research topic. Lipreading is the recognition of what someone is saying using visual information, primarily lip movements. In this study, we created a custom...

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Dynamic relationship between volume and volatility in the Chinese stock market: Evidence from the MS-VAR model

Since market uncertainty, or volatility, serves as a crucial gauge for assessing the traits of market fluctuations, the link between stock market volume and price continues to be a focal point of interest...

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Joint decision-making of virtual module formation and scheduling considering queuing time

Formation and scheduling are the most important decisions in the virtual modular manufacturing system; however, the global performance optimization of the system may be sacrificed via the superposition...

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Explainable prediction of loan default based on machine learning models

Owing to the convenience of online loans, an increasing number of people are borrowing money on online platforms. With the emergence of machine learning technology, predicting loan defaults has become...

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Blockchain and its derived technologies shape the future generation of digital businesses: a focus on decentralized finance and the Metaverse

Without a doubt, blockchain, as one of the most valuable technological advancements, has been introduced over the past decade and has played a significant role in the industrial revolution. The emergence...

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The impact of the digital economy on the servitization of industrial structures: the moderating effect of human capital

The digital economy, which was born during the late third technological revolution, has caused significant economic and societal changes. Amid sluggish global economic growth, China’s economy is facing...

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Systematic review of data-centric approaches in artificial intelligence and machine learning

Artificial intelligence (AI) relies on data and algorithms. State-of-the-art (SOTA) AI smart algorithms have been developed to improve the performance of AI-oriented structures. However, model-centric...

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Novel method for ranking batsmen in Indian Premier League

Sports analytics have benefited immensely from the growth and popularity of artificial intelligence and machine learning. These techniques enable sports analysts to evaluate player performance more...

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Investigating customer churn in banking: A machine learning approach and visualization app for data science and management

Customer attrition in the banking industry occurs when consumers quit using the goods and services offered by the bank for some time and, after that, end their connection with the bank. Therefore, customer...

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Hotspots and trends of environmental, social and governance (ESG) research: a bibliometric analysis

This study examines paper-level metrics in the literature on topics related to environmental, social and governance (ESG) to provide a research agenda for hotspots and trends. Based on 755 papers on...

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A trajectory data warehouse solution for workforce management decision-making

In modern workforce management, the demand for new ways to maximize worker satisfaction, productivity, and security levels is endless. Workforce movement data such as those source data from an access...

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