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Demand Forecasting

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Showing 151–200 of 212 papers

TitleStatusHype
SPADE Split Peak Attention DEcomposition—0
Sparse Regularization in Marketing and Economics—0
Spatio-temporal Parking Behaviour Forecasting and Analysis Before and During COVID-19—0
Stacking for Probabilistic Short-term Load Forecasting—0
STARdom: an architecture for trusted and secure human-centered manufacturing systems—0
State-Space Models Win the IEEE DataPort Competition on Post-covid Day-ahead Electricity Load Forecasting—0
Stochastic MPC for energy hubs using data driven demand forecasting—0
Systematic review of deep learning and machine learning for building energy—0
Tab2vox: CNN-Based Multivariate Multilevel Demand Forecasting Framework by Tabular-To-Voxel Image Conversion—0
Taxi demand forecasting: A HEDGE based tessellation strategy for improved accuracy—0
Textual-Knowledge-Guided Numerical Feature Discovery Method for Power Demand Forecasting—0
The Potential of Large Language Models in Supply Chain Management: Advancing Decision-Making, Efficiency, and Innovation—0
Time series forecasting with high stakes: A field study of the air cargo industry—0
Topology-based Clusterwise Regression for User Segmentation and Demand Forecasting—0
Tourism Demand Forecasting: An Ensemble Deep Learning Approach—0
Towards Active Learning Based Smart Assistant for Manufacturing—0
Towards Data-Driven Electricity Management: Multi-Region Harmonized Data and Knowledge Graph—0
Towards Universal Large-Scale Foundational Model for Natural Gas Demand Forecasting—0
Transfer Learning in Transformer-Based Demand Forecasting For Home Energy Management System—0
Tsformer: Time series Transformer for tourism demand forecasting—0
Univariate Long-Term Municipal Water Demand Forecasting—0
Unsupervised Knowledge Adaptation for Passenger Demand Forecasting—0
Utilizing artificial neural networks to predict demand for weather-sensitive products at retail stores—0
Utilizing Device-level Demand Forecasting for Flexibility Markets - Full Version—0
Why do zeroes happen? A model-based approach for demand classification—0
XAI-KG: knowledge graph to support XAI and decision-making in manufacturing—0
XRMDN: An Extended Recurrent Mixture Density Network for Short-Term Probabilistic Rider Demand Forecasting with High Volatility—0
Deep Learning based Forecasting: a case study from the online fashion industry—0
A Bayesian Approach for Predicting Food and Beverage Sales in Staff Canteens and Restaurants—0
PA-CFL: Privacy-Adaptive Clustered Federated Learning for Transformer-Based Sales Forecasting on Heterogeneous Retail Data—0
A Clustering-aided Ensemble Method for Predicting Ridesourcing Demand in Chicago—0
A Comprehensive Forecasting Framework based on Multi-Stage Hierarchical Forecasting Reconciliation and Adjustment—0
A Context Integrated Relational Spatio-Temporal Model for Demand and Supply Forecasting—0
Actionable Cognitive Twins for Decision Making in Manufacturing—0
A Daily Tourism Demand Prediction Framework Based on Multi-head Attention CNN: The Case of The Foreign Entrant in South Korea—0
Adaptive Digital Twin and Communication-Efficient Federated Learning Network Slicing for 5G-enabled Internet of Things—0
Advancing Retail Data Science: Comprehensive Evaluation of Synthetic Data—0
AI-Based Demand Forecasting and Load Balancing for Optimising Energy use in Healthcare Systems: A real case study—0
Algorithmic Decision-Making Safeguarded by Human Knowledge—0
A machine learning approach to itinerary-level booking prediction in competitive airline markets—0
A New Decomposition Ensemble Approach for Tourism Demand Forecasting: Evidence from Major Source Countries—0
An Exponential Factorization Machine with Percentage Error Minimization to Retail Sales Forecasting—0
A novel forecasting framework combining virtual samples and enhanced Transformer models for tourism demand forecasting—0
A Novel Hybrid Approach to Contraceptive Demand Forecasting: Integrating Point Predictions with Probabilistic Distributions—0
Towards More Efficient Shared Autonomous Mobility: A Learning-Based Fleet Repositioning Approach—0
An XGBoost-Based Forecasting Framework for Product Cannibalization—0
Application-Driven Learning: A Closed-Loop Prediction and Optimization Approach Applied to Dynamic Reserves and Demand Forecasting—0
Application of Deep Learning Long Short-Term Memory in Energy Demand Forecasting—0
Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale—0
News and Load: A Quantitative Exploration of Natural Language Processing Applications for Forecasting Day-ahead Electricity System Demand—0
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