Cover Image

Regression Models Meet Foundation Models: A Hybrid-AI Approach to Practical Electricity Price Forecasting

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Qiu, Yunzhong, Li, Binzhu, Wei, Hao, Weng, Shenglin, Wang, Chen, Pei, Zhongyi, Long, Mingsheng, Wang, Jianmin
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

TimesBERT: A BERT-Style Foundation Model for Time Series Understanding
by: Zhang, Haoran, et al.
Published: (2025)

Adapt Data to Model: Adaptive Transformation Optimization for Domain-shared Time Series Foundation Models
by: Qiu, Yunzhong, et al.
Published: (2026)

DiTS: Multimodal Diffusion Transformers Are Time Series Forecasters
by: Zhang, Haoran, et al.
Published: (2026)

TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling
by: Dong, Jiaxiang, et al.
Published: (2024)

DualWeaver: Synergistic Feature Weaving Surrogates for Multivariate Forecasting with Univariate Time Series Foundation Models
by: Li, Jinpeng, et al.
Published: (2026)

TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables
by: Wang, Yuxuan, et al.
Published: (2024)

Domain Guidance: A Simple Transfer Approach for a Pre-trained Diffusion Model
by: Zhong, Jincheng, et al.
Published: (2025)

AutoTimes: Autoregressive Time Series Forecasters via Large Language Models
by: Liu, Yong, et al.
Published: (2024)

PriceFM: Foundation Model for Probabilistic Electricity Price Forecasting
by: Yu, Runyao, et al.
Published: (2025)

Timer-XL: Long-Context Transformers for Unified Time Series Forecasting
by: Liu, Yong, et al.
Published: (2024)

CoRA: Covariate-Aware Adaptation of Time Series Foundation Models
by: Qin, Guo, et al.
Published: (2025)

Sundial: A Family of Highly Capable Time Series Foundation Models
by: Liu, Yong, et al.
Published: (2025)

CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding
by: Chen, Kaiyuan, et al.
Published: (2024)

Metadata Matters for Time Series: Informative Forecasting with Transformers
by: Dong, Jiaxiang, et al.
Published: (2024)

Day-Ahead Electricity Price Forecasting for Volatile Markets Using Foundation Models with Regularization Strategy
by: Ponyuenyong, Kritchanat, et al.
Published: (2026)

Boosting AI Reliability with an FSM-Driven Streaming Inference Pipeline: An Industrial Case
by: Zhang, Yutian, et al.
Published: (2026)

Hybrid Approach for Electricity Price Forecasting using AlexNet and LSTM
by: Sambana, Bosubabu, et al.
Published: (2025)

CompilerDream: Learning a Compiler World Model for General Code Optimization
by: Deng, Chaoyi, et al.
Published: (2024)

Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Models
by: Guo, Xingzhuo, et al.
Published: (2025)

Deep Time Series Models: A Comprehensive Survey and Benchmark
by: Wang, Yuxuan, et al.
Published: (2024)

Assessing the Performance-Efficiency Trade-off of Foundation Models in Probabilistic Electricity Price Forecasting
by: Lettner, Jan Niklas, et al.
Published: (2026)

PhySense: Sensor Placement Optimization for Accurate Physics Sensing
by: Ma, Yuezhou, et al.
Published: (2025)

ProPINN: Demystifying Propagation Failures in Physics-Informed Neural Networks
by: Wu, Haixu, et al.
Published: (2025)

Deep Time-Series Models Meet Volatility: Multi-Horizon Electricity Price Forecasting in the Australian National Electricity Market
by: Gani, Mohammed Osman, et al.
Published: (2026)

Timer-S1: A Billion-Scale Time Series Foundation Model with Serial Scaling
by: Liu, Yong, et al.
Published: (2026)

Machine Learning and Deep Learning Models for Short Term Electricity Price Forecasting in Australia's National Electricity Market
by: Lu, Wei, et al.
Published: (2026)

Timer: Generative Pre-trained Transformers Are Large Time Series Models
by: Liu, Yong, et al.
Published: (2024)

BTTackler: A Diagnosis-based Framework for Efficient Deep Learning Hyperparameter Optimization
by: Pei, Zhongyi, et al.
Published: (2026)

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

TiMi: Empower Time Series Transformers with Multimodal Mixture of Experts
by: Lin, Jiafeng, et al.
Published: (2026)

Empirical evaluation of Time Series Foundation Models for Day-ahead and Imbalance Electricity Price Forecasting in Belgium
by: Bui, Chi, et al.
Published: (2026)

HarmonyDream: Task Harmonization Inside World Models
by: Ma, Haoyu, et al.
Published: (2023)

Functional Factor Regression with an Application to Electricity Price Curve Modeling
by: Otto, Sven, et al.
Published: (2025)

The Promise of Time-Series Foundation Models for Agricultural Forecasting: Evidence from Commodity Prices
by: Wang, Le, et al.
Published: (2026)

Transolver: A Fast Transformer Solver for PDEs on General Geometries
by: Wu, Haixu, et al.
Published: (2024)

Transolver-3: Scaling Up Transformer Solvers to Industrial-Scale Geometries
by: Zhou, Hang, et al.
Published: (2026)

Enhancing Electricity Price Prediction Accuracy With an Attention Mechanism‐ LSTM Hybrid Model
by: Huidan Zhuo, et al.
Published: (2026)

Electricity Spot Prices Forecasting Using Stochastic Volatility Models
by: Batyrov, Andrei Renatovich
Published: (2024)

Online Multivariate Regularized Distributional Regression for High-dimensional Probabilistic Electricity Price Forecasting
by: Hirsch, Simon
Published: (2025)

HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction
by: Xing, Lanxiang, et al.
Published: (2023)