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Machine Learning and Deep Learning-Based Students’ Grade Prediction
Predicting student performance in a curriculum or program offers the prospect of improving academic outcomes. By using effective performance...
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Deep learning, textual sentiment, and financial market
In this paper, we apply the BERT model, a cut-edging deep learning model, to construct a novel textual sentiment index in the Chinese stock market....
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Image deep learning in fault diagnosis of mechanical equipment
With the development of industry, more and more crucial mechanical machinery generate wildness demand of effective fault diagnosis to ensure the safe...
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Comparing Machine Learning and Deep Learning Techniques for Text Analytics: Detecting the Severity of Hate Comments Online
Social media platforms have become an increasingly popular tool for individuals to share their thoughts and opinions with other people. However, very...
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Forecasting oil price in times of crisis: a new evidence from machine learning versus deep learning models
This study investigates oil price forecasting during a time of crisis, from December 2007 to December 2021. As the oil market has experienced various...
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Multi-echelon inventory optimization using deep reinforcement learning
This paper studies the applicability of a deep reinforcement learning approach to three different multi-echelon inventory systems, with the objective...
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Machine learning vs deep learning in stock market investment: an international evidence
Machine learning and deep learning are powerful tools for quantitative investment. To examine the effectiveness of the models in different markets,...
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Designing an adaptive and deep learning based control framework for modular production systems
In today’s rapidly changing production landscape with increasingly complex manufacturing processes and shortening product life cycles, a company’s...
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Deep reinforcement learning imbalanced credit risk of SMEs in supply chain finance
It is crucial to predict the credit risk of small and medium-sized enterprises (SMEs) accurately for the success of supply chain finance (SCF)....
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Automated assembly quality inspection by deep learning with 2D and 3D synthetic CAD data
In the manufacturing industry, automatic quality inspections can lead to improved product quality and productivity. Deep learning-based computer...
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High-dimensional stochastic control models for newsvendor problems and deep learning resolution
This paper studies continuous-time models for newsvendor problems with dynamic replenishment, financial hedging and Stackelberg competition. These...
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Visual coating inspection framework via self-labeling and multi-stage deep learning strategies
An instantaneous and precise coating inspection method is imperative to mitigate the risk of flaws, defects, and discrepancies on coated surfaces....
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Deep learning-based conductive particle inspection for TFT-LCDs inspired by parametric space envelope
The inspection of conductive particles after Anisotropic Conductive Film bonding is a crucial step in TFT-LCD manufacturing for quality assurance....
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COVID-19 Fake News Detection using Deep Learning Model
People may now receive and share information more quickly and easily than ever due to the widespread use of mobile networked devices. However, this...
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Deep reinforcement learning for dynamic scheduling of energy-efficient automated guided vehicles
Automated guided vehicle (AGV) scheduling has become a hot topic in recent years as manufacturing systems become flexible and intelligent. However,...
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Crew recovery optimization with deep learning and column generation for sustainable airline operation management
In today’s competitive marketplace, businesses face the ongoing challenge of meeting evolving customer demands while maintaining sustainable...
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The third party logistics provider freight management problem: a framework and deep reinforcement learning approach
In many large manufacturing companies, freight management is handled by a third-party logistics (3PL) provider, thus allowing manufacturers and their...
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Develo** an explainable hybrid deep learning model in digital transformation: an empirical study
Automated inspection is an important component of digital transformation. However, most deep learning models that have been widely applied in...
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Forecasting commodity prices: empirical evidence using deep learning tools
Since the last two decades, financial markets have exhibited several transformations owing to recurring crises episodes that has led to the...
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Deep learning based condition monitoring of road traffic for enhanced transportation routing
The efficient management of road traffic is crucial for enhancing transportation routing and improving overall traffic flow. However, the...
