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Demand Forecasting

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Showing 26–50 of 212 papers

TitleStatusHype
Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating SparsityCode0
High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula ProcessesCode0
Leveraging World Events to Predict E-Commerce Consumer Demand under AnomalyCode0
Forecasting time series with constraintsCode0
Multi-way Interacting Regression via Factorization MachinesCode0
Global Rewards in Multi-Agent Deep Reinforcement Learning for Autonomous Mobility on Demand SystemsCode0
Demand Forecasting from Spatiotemporal Data with Graph Networks and Temporal-Guided EmbeddingCode0
Forecasting railway ticket demand with search query open dataCode0
Graph Construction with Flexible Nodes for Traffic Demand PredictionCode0
Multivariate Arrival Times with Recurrent Neural Networks for Personalized Demand ForecastingCode0
Temporal Regularized Matrix Factorization for High-dimensional Time Series PredictionCode0
A Scalable and Transferable Time Series Prediction Framework for Demand Forecasting—0
Artificial Intelligence and Statistical Techniques in Short-Term Load Forecasting: A Review—0
AI-Based Demand Forecasting and Load Balancing for Optimising Energy use in Healthcare Systems: A real case study—0
ARMDN: Associative and Recurrent Mixture Density Networks for eRetail Demand Forecasting—0
News and Load: A Quantitative Exploration of Natural Language Processing Applications for Forecasting Day-ahead Electricity System Demand—0
Advancing Retail Data Science: Comprehensive Evaluation of Synthetic Data—0
A Context Integrated Relational Spatio-Temporal Model for Demand and Supply Forecasting—0
Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale—0
Application of Deep Learning Long Short-Term Memory in Energy Demand Forecasting—0
Deep Learning for Energy Time-Series Analysis and Forecasting—0
Deep Convolutional Neural Networks for Short-Term Multi-Energy Demand Prediction of Integrated Energy Systems—0
Application-Driven Learning: A Closed-Loop Prediction and Optimization Approach Applied to Dynamic Reserves and Demand Forecasting—0
A Comprehensive Forecasting Framework based on Multi-Stage Hierarchical Forecasting Reconciliation and Adjustment—0
A Bayesian Approach for Predicting Food and Beverage Sales in Staff Canteens and Restaurants—0
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