---
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id: "24ea13c732146e2c4412b2212a2a86bc68cd6cfe6f9c0e79cf1b10a4e728fa62"
canonical_url: "https://aidr.today/24ea13c7?lang=en"
title: "Comparative review of hybrid forecasting models for short-term prediction of building thermal load"
lang: "en"
requested_lang: "en"
available_langs: ["en","vi"]
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published_at: "2026-10-07T04:00:00.000Z"
category: "Research"
topics: ["inference"]
source_urls: ["https://arxiv.org/abs/2610.06881"]
summary: "A comparative review of 13 hybrid models for short-term building thermal load forecasting identifies the EMD-LSTM-Markov model as achieving the highest accuracy in predicting day-ahead heating and DHW demand patterns, though high power swells and spikes are underestimated. The assessment uses historical thermal demand data from Scottish households and weather forecasts to evaluate data-driven models enhanced with state-of-the-art techniques."
---

# Comparative review of hybrid forecasting models for short\-term prediction of building thermal load

> [Open the canonical story](<https://aidr.today/24ea13c7?lang=en>)

**Published:** 2026-10-07T04:00:00.000Z
**Category:** Research
**Topics:** inference

## Summary

A comparative review of 13 hybrid models for short\-term building thermal load forecasting identifies the EMD\-LSTM\-Markov model as achieving the highest accuracy in predicting day\-ahead heating and DHW demand patterns, though high power swells and spikes are underestimated\. The assessment uses historical thermal demand data from Scottish households and weather forecasts to evaluate data\-driven models enhanced with state\-of\-the\-art techniques\.

## Sources

- [Story source](<https://arxiv.org/abs/2610.06881>)