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Product backorder prediction using deep neural network on imbalanced data
11 references·14 citing·51 second hop
Product backorder prediction using deep neural network on imbalanced data (2021)Product backorder prediction using deep n…Prediction of probable backorder scenarios in the supply chain using Distributed Random Forest and Gradient Boosting Machine learning techniques (2020)Prediction of probable backor…Two-stage consumer credit risk modelling using heterogeneous ensemble learning (2019)Two-stage consumer credit ris…Deep learning in business analytics and operations research: Models, applications and managerial implications (2019)Deep learning in business ana…Control chart pattern recognition using the convolutional neural network (2019)Control chart pattern recogni…Exploring the use of deep neural networks for sales forecasting in fashion retail (2018)Exploring the use of deep neu…Applying machine learning to the dynamic selection of replenishment policies in fast-changing supply chain environments (2018)Applying machine learning to …Big Data Analytics in Operations Management (2017)Big Data Analytics in Operati…A Deep Learning Approach for Predicting Process Behaviour at Runtime (2017)A Deep Learning Approach for …Deep Learning for Finance: Deep Portfolios (2016)Deep Learning for Finance: De…Development and application of consumer credit scoring models using profit-based classification measures (2014)Development and application o…A reinforcement learning model for supply chain ordering management: An application to the beer game (2008)A reinforcement learning mode…Leveraging synthetic data to tackle machine learning challenges in supply chains: challenges, methods, applications, and research opportunities (2025)Leveraging synthetic data to …Performance of deep reinforcement learning algorithms in two-echelon inventory control systems (2024)Performance of deep reinforce…Advancing credit risk modelling with Machine Learning: A comprehensive review of the state-of-the-art (2024)Advancing credit risk modelli…A blending ensemble learning model for crude oil price forecasting (2024)A blending ensemble learning …Supply Chain 4.0: A Machine Learning-Based Bayesian-Optimized LightGBM Model for Predicting Supply Chain Risk (2023)Supply Chain 4.0: A Machine L…QAmplifyNet: pushing the boundaries of supply chain backorder prediction using interpretable hybrid quantum-classical neural network (2023)QAmplifyNet: pushing the boun…Multi-period portfolio optimization using a deep reinforcement learning hyper-heuristic approach (2023)Multi-period portfolio optimi…Integration of Artificial Intelligence Technology in Management Accounting Information System: An Empirical Study (2023)Integration of Artificial Int…Cryptocurrency price forecasting – A comparative analysis of ensemble learning and deep learning methods (2023)Cryptocurrency price forecast…Applications of deep learning into supply chain management: a systematic literature review and a framework for future research (2022)Applications of deep learning…An optimized decomposition integration framework for carbon price prediction based on multi-factor two-stage feature dimension reduction (2022)An optimized decomposition in…Deep learning-based exchange rate prediction during the COVID-19 pandemic (2021)Deep learning-based exchange …An Explainable Machine Learning Model for Material Backorder Prediction in Inventory Management (2021)An Explainable Machine Learni…An Automatic Credit Scoring Strategy (ACSS) using memetic evolutionary algorithm and neural architecture search (2021)An Automatic Credit Scoring S…Credit Scoring and Its Applications (2002)Benchmarking state-of-the-art classification algorithms for credit scoring (2003)New insights into churn prediction in the telecommunication sector: A profit driven data mining approach (2011)Cost-based feature selection for Support Vector Machines: An application in credit scoring (2017)Predicting mortgage default using convolutional neural networks (2018)Modeling Managerial Behavior: Misperceptions of Feedback in a Dynamic Decision Making 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disruption risks and resilience in the era of Industry 4.0 (2020)Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case (2020)Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic (2020)Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)Deep learning with long short-term memory networks for financial market predictions (2017)Deep learning for detecting financial statement fraud (2020)Artificial intelligence applications in supply chain management (2021)Deep learning for credit scoring: Do or don’t? (2021)Fuzzy sets (1965)Time Series Analysis: Forecasting and Control (1977)Fuzzy sets (1996)Portfolio formation with preselection using deep learning from long-term financial data (2019)A hybrid stock price index forecasting model based on variational mode decomposition and LSTM network (2020)Time-series forecasting of seasonal items sales using machine learning – A comparative analysis (2022)International Journal of Production Research (1962)DEFINING SUPPLY CHAIN MANAGEMENT (2001)Digital Supply Chain Twins: Managing the Ripple Effect, Resilience, and Disruption Risks by Data-Driven Optimization, Simulation, and Visibility (2019)Fusion-Based Supply Chain Collaboration Using Machine Learning Techniques (2021)Artificial intelligence in supply chain and operations management: a multiple case study research (2023)Collateral and Rationing: Sorting Equilibria in Monopolistic and Competitive Credit Markets (1987)A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)Credit scoring based on tree-enhanced gradient boosting decision trees (2021)Assessing credit risk of commercial customers using hybrid machine learning algorithms (2022)A multilayer stacking method base on RFE-SHAP feature selection strategy for recognition of driver’s mental load and emotional state (2023)Time series forecasting using a hybrid ARIMA and neural network model (2003)Another look at measures of forecast accuracy (2006)A framework of sustainable supply chain management: moving toward new theory (2008)Supply chain risk management with machine learning technology: A literature review and future research directions (2022)Data science and big data analytics: a systematic review of methodologies used in the supply chain and logistics research (2023)Comparing Predictive Accuracy (1994)Comparing Predictive Accuracy (2002)A sentiment-enhanced hybrid model for crude oil price forecasting (2022)A Systematic Survey of AI Models in Financial Market Forecasting for Profitability Analysis (2023)
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References

  • 2017Big Data Analytics in Operations Management1,023 cited
  • 2016Deep Learning for Finance: Deep Portfolios765 cited
  • 2019Deep learning in business analytics and operations research: Models, applications and managerial implications391 cited
  • 2018Exploring the use of deep neural networks for sales forecasting in fashion retail262 cited
  • 2019Two-stage consumer credit risk modelling using heterogeneous ensemble learning182 cited
  • 2014Development and application of consumer credit scoring models using profit-based classification measures179 cited
  • 2020Prediction of probable backorder scenarios in the supply chain using Distributed Random Forest and Gradient Boosting Machine learning techniques167 cited
  • 2018Applying machine learning to the dynamic selection of replenishment policies in fast-changing supply chain environments166 cited
  • 2008A reinforcement learning model for supply chain ordering management: An application to the beer game148 cited
  • 2019Control chart pattern recognition using the convolutional neural network114 cited
  • 2017A Deep Learning Approach for Predicting Process Behaviour at Runtime105 cited

Cited by

  • 2021Deep learning-based exchange rate prediction during the COVID-19 pandemic134 cited
  • 2022Applications of deep learning into supply chain management: a systematic literature review and a framework for future research98 cited

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  • 2023Cryptocurrency price forecasting – A comparative analysis of ensemble learning and deep learning methods91 cited
  • 2023Multi-period portfolio optimization using a deep reinforcement learning hyper-heuristic approach77 cited
  • 2021An Explainable Machine Learning Model for Material Backorder Prediction in Inventory Management50 cited
  • 2022An optimized decomposition integration framework for carbon price prediction based on multi-factor two-stage feature dimension reduction50 cited
  • 2024A blending ensemble learning model for crude oil price forecasting48 cited
  • 2024Advancing credit risk modelling with Machine Learning: A comprehensive review of the state-of-the-art42 cited
  • 2023QAmplifyNet: pushing the boundaries of supply chain backorder prediction using interpretable hybrid quantum-classical neural network40 cited
  • 2025Leveraging synthetic data to tackle machine learning challenges in supply chains: challenges, methods, applications, and research opportunities40 cited
  • 2023Integration of Artificial Intelligence Technology in Management Accounting Information System: An Empirical Study35 cited
  • 2024Performance of deep reinforcement learning algorithms in two-echelon inventory control systems32 cited
  • 2023Supply Chain 4.0: A Machine Learning-Based Bayesian-Optimized LightGBM Model for Predicting Supply Chain Risk31 cited
  • 2021An Automatic Credit Scoring Strategy (ACSS) using memetic evolutionary algorithm and neural architecture search27 cited