Cover Image

Energy Price Modelling: A Comparative Evaluation of four Generations of Forecasting Methods

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Andrei, Alexandru-Victor, Velev, Georg, Toma, Filip-Mihai, Pele, Daniel Traian, Lessmann, Stefan
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Neural Architecture Search for global multi-step Forecasting of Energy Production Time Series
by: Velev, Georg, et al.
Published: (2025)

Interpretable, multi-dimensional Evaluation Framework for Causal Discovery from observational i.i.d. Data
by: Velev, Georg, et al.
Published: (2024)

Causality analysis of electricity market liberalization on electricity price using novel Machine Learning methods
by: Shahar, Orr, et al.
Published: (2025)

The Deep Promotion Time Cure Model
by: Medina-Olivares, Victor, et al.
Published: (2023)

Quantum-Optimized Selective State Space Model for Efficient Time Series Prediction
by: Jura, Stefan-Alexandru, et al.
Published: (2025)

Deep Learning and NLP in Cryptocurrency Forecasting: Integrating Financial, Blockchain, and Social Media Data
by: Gurgul, Vincent, et al.
Published: (2023)

Incorporating data drift to perform survival analysis on credit risk
by: Peng, Jianwei, et al.
Published: (2026)

Fighting Sampling Bias: A Framework for Training and Evaluating Credit Scoring Models
by: Kozodoi, Nikita, et al.
Published: (2024)

Quantum-Enhanced Weight Optimization for Neural Networks Using Grover's Algorithm
by: Jura, Stefan-Alexandru, et al.
Published: (2025)

Meta-learning how to Share Credit among Macro-Actions
by: Hosu, Ionel-Alexandru, et al.
Published: (2025)

Leveraging Zero-Shot Prompting for Efficient Language Model Distillation
by: Vöge, Lukas, et al.
Published: (2024)

Semi-structured multi-state delinquency model for mortgage default
by: Medina-Olivares, Victor, et al.
Published: (2026)

Leveraging Generative AI for Enhancing Automated Assessment in Programming Education Contests
by: Dascalescu, Stefan, et al.
Published: (2025)

Uplift modeling with continuous treatments: A predict-then-optimize approach
by: De Vos, Simon, et al.
Published: (2024)

Variational Quantum Circuit-Based Reinforcement Learning for Dynamic Portfolio Optimization
by: Gurgul, Vincent, et al.
Published: (2026)

Transfer Learning for Loan Recovery Prediction under Distribution Shifts with Heterogeneous Feature Spaces
by: Gerling, Christopher, et al.
Published: (2026)

Semi-Supervised Learning for Large Language Models Safety and Content Moderation
by: Dinuta, Eduard Stefan, et al.
Published: (2025)

Air Pollution Forecasting in Bucharest
by: Şerban, Dragoş-Andrei, et al.
Published: (2025)

Causal Forecasting for Pricing
by: Schultz, Douglas, et al.
Published: (2023)

A Comparative Study of Machine Learning Algorithms for Electricity Price Forecasting with LIME-Based Interpretability
by: Zhao, Xuanyi, et al.
Published: (2025)

Comparative Evaluation of Weather Forecasting using Machine Learning Models
by: Rahman, Md Saydur, et al.
Published: (2024)

Data-driven Calibration Sample Selection and Forecast Combination in Electricity Price Forecasting: An Application of the ARHNN Method
by: Serafin, Tomasz, et al.
Published: (2025)

News-Driven Stock Price Forecasting in Indian Markets: A Comparative Study of Advanced Deep Learning Models
by: Attaluri, Kaushal, et al.
Published: (2024)

Optimising Battery Energy Storage System Trading via Energy Market Operator Price Forecast
by: Fabre, Aymeric
Published: (2025)

TabEBM: A Tabular Data Augmentation Method with Distinct Class-Specific Energy-Based Models
by: Margeloiu, Andrei, et al.
Published: (2024)

Transfer Learning on Transformers for Building Energy Consumption Forecasting -- A Comparative Study
by: Spencer, Robert, et al.
Published: (2024)

Forecasting Day-Ahead Electricity Prices in the Integrated Single Electricity Market: Addressing Volatility with Comparative Machine Learning Methods
by: Harkin, Ben, et al.
Published: (2024)

Trend-Adjusted Time Series Models with an Application to Gold Price Forecasting
by: Kazemdehbashi, Sina
Published: (2026)

Learning Pareto manifolds in high dimensions: How can regularization help?
by: Wegel, Tobias, et al.
Published: (2025)

Applications of fractional calculus in learned optimization
by: Szente, Teodor Alexandru, et al.
Published: (2024)

How the Optimizer Shapes Learned Solutions in Equivariant Neural Networks
by: Stupariu, Teodor-Mihai, et al.
Published: (2026)

From Distributional to Quantile Neural Basis Models: the case of Electricity Price Forecasting
by: Brusaferri, Alessandro, et al.
Published: (2025)

Electricity Price Forecasting: Bridging Linear Models, Neural Networks and Online Learning
by: Mahtout, Btissame El, et al.
Published: (2026)

Generative and Nonparametric Approaches for Conditional Distribution Estimation: Methods, Perspectives, and Comparative Evaluations
by: Chin, Yen-Shiu, et al.
Published: (2026)

A Transformer approach for Electricity Price Forecasting
by: Llorente, Oscar, et al.
Published: (2024)

GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
by: Aksu, Taha, et al.
Published: (2024)

Foundation Models for Credit Risk Prediction: A Game Changer?
by: Baesens, Bart, et al.
Published: (2026)

Network Degeneracy as an Indicator of Training Performance: Comparing Finite and Infinite Width Angle Predictions
by: Jakub, Cameron, et al.
Published: (2023)

Forecasting Electricity Prices
by: Maciejowska, Katarzyna, et al.
Published: (2022)

Comparative Evaluation of Clustered Federated Learning Methods
by: Ali, Michael Ben, et al.
Published: (2024)