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Demand Forecasting

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Showing 51–100 of 212 papers

TitleStatusHype
GUIM -- General User and Item Embedding with Mixture of Representation in E-commerce—0
Deep Neural Networks for Choice Analysis: A Statistical Learning Theory Perspective—0
Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties—0
Deep Reinforcement Learning-Assisted Federated Learning for Robust Short-term Utility Demand Forecasting in Electricity Wholesale Markets—0
Deep Convolutional Neural Networks for Short-Term Multi-Energy Demand Prediction of Integrated Energy Systems—0
DeepSTCL: A Deep Spatio-temporal ConvLSTM for Travel Demand Prediction—0
Demand Forecasting for Electric Vehicle Charging Stations using Multivariate Time-Series Analysis—0
Demand Forecasting for Platelet Usage: from Univariate Time Series to Multivariate Models—0
Demand Forecasting in Smart Grid Using Long Short-Term Memory—0
Demand Forecasting in Supply Chain Management for Rossmann Stores Using Weather Enhanced Deep Learning Model—0
Demand Forecasting of Individual Probability Density Functions with Machine Learning—0
Demand forecasting techniques for build-to-order lean manufacturing supply chains—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
Data Pre-Processing and Evaluating the Performance of Several Data Mining Methods for Predicting Irrigation Water Requirement—0
GNN-based Probabilistic Supply and Inventory Predictions in Supply Chain Networks—0
An XGBoost-Based Forecasting Framework for Product Cannibalization—0
Consumer Transactions Simulation through Generative Adversarial Networks—0
GEANN: Scalable Graph Augmentations for Multi-Horizon Time Series Forecasting—0
Towards More Efficient Shared Autonomous Mobility: A Learning-Based Fleet Repositioning Approach—0
Adaptive Digital Twin and Communication-Efficient Federated Learning Network Slicing for 5G-enabled Internet of Things—0
Combining time-series and textual data for taxi demand prediction in event areas: a deep learning approach—0
Combining Individual and Joint Networking Behavior for Intelligent IoT Analytics—0
A Novel Hybrid Approach to Contraceptive Demand Forecasting: Integrating Point Predictions with Probabilistic Distributions—0
Combating the Bullwhip Effect in Rival Online Food Delivery Platforms Using Deep Learning—0
Fairness-Enhancing Vehicle Rebalancing in the Ride-hailing System—0
Fairness-enhancing deep learning for ride-hailing demand prediction—0
Causal Forecasting for Pricing—0
A novel forecasting framework combining virtual samples and enhanced Transformer models for tourism demand forecasting—0
Federated Dynamic Modeling and Learning for Spatiotemporal Data Forecasting—0
Federated Graph Learning for EV Charging Demand Forecasting with Personalization Against Cyberattacks—0
F-FOMAML: GNN-Enhanced Meta-Learning for Peak Period Demand Forecasting with Proxy Data—0
Flight Demand Forecasting with Transformers—0
A Clustering-aided Ensemble Method for Predicting Ridesourcing Demand in Chicago—0
Exploring the impact of weather on Metro demand forecasting using machine learning method—0
Exploring Quantum Neural Networks for Demand Forecasting—0
Bayesian Intermittent Demand Forecasting for Large Inventories—0
Generative AI in Transportation Planning: A Survey—0
GeoTransformer: Enhancing Urban Forecasting with Dependency Retrieval and Geospatial Attention—0
Ensemble Forecasting of Monthly Electricity Demand using Pattern Similarity-based Methods—0
Enriching Artificial Intelligence Explanations with Knowledge Fragments—0
Traveller behaviour in public transport in the early stages of the COVID-19 pandemic in the Netherlands—0
An Exponential Factorization Machine with Percentage Error Minimization to Retail Sales Forecasting—0
Travel Demand Forecasting: A Fair AI Approach—0
Improving Demand Forecasting in Open Systems with Cartogram-Enhanced Deep Learning—0
AutoML Algorithms for Online Generalized Additive Model Selection: Application to Electricity Demand Forecasting—0
H-FLTN: A Privacy-Preserving Hierarchical Framework for Electric Vehicle Spatio-Temporal Charge Prediction—0
Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting—0
Energy Predictive Models with Limited Data using Transfer Learning—0
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