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Demand Forecasting

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Showing 101–125 of 212 papers

TitleStatusHype
Masked Multi-Step Multivariate Time Series Forecasting with Future Information—0
Tab2vox: CNN-Based Multivariate Multilevel Demand Forecasting Framework by Tabular-To-Voxel Image Conversion—0
MQRetNN: Multi-Horizon Time Series Forecasting with Retrieval Augmentation—0
GUIM -- General User and Item Embedding with Mixture of Representation in E-commerce—0
Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand PredictionCode1
Learning Citywide Patterns of Life from Trajectory Monitoring—0
Deep Reinforcement Learning-Assisted Federated Learning for Robust Short-term Utility Demand Forecasting in Electricity Wholesale Markets—0
A deep inverse reinforcement learning approach to route choice modeling with context-dependent rewardsCode1
Unsupervised Knowledge Adaptation for Passenger Demand Forecasting—0
Practical Skills Demand Forecasting via Representation Learning of Temporal Dynamics—0
Enriching Artificial Intelligence Explanations with Knowledge Fragments—0
Optimizing Revenue Maximization and Demand Learning in Airline Revenue Management—0
Combining Individual and Joint Networking Behavior for Intelligent IoT Analytics—0
Systematic review of deep learning and machine learning for building energy—0
LIMREF: Local Interpretable Model Agnostic Rule-based Explanations for Forecasting, with an Application to Electricity Smart Meter Data—0
Artificial Intelligence and Statistical Techniques in Short-Term Load Forecasting: A Review—0
Optimal Latent Space Forecasting for Large Collections of Short Time Series Using Temporal Matrix Factorization—0
A Daily Tourism Demand Prediction Framework Based on Multi-head Attention CNN: The Case of The Foreign Entrant in South Korea—0
Machine Learning for Air Transport Planning and Management—0
Federated Deep Learning in Electricity Forecasting: An MCDM Approach—0
An XGBoost-Based Forecasting Framework for Product Cannibalization—0
Flight Demand Forecasting with Transformers—0
State-Space Models Win the IEEE DataPort Competition on Post-covid Day-ahead Electricity Load Forecasting—0
A Clustering-aided Ensemble Method for Predicting Ridesourcing Demand in Chicago—0
Model retraining and information sharing in a supply chain with long-term fluctuating demands—0
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