Scholarlink

This paper presents an application of Long Short-Term Memory (LSTM) recurrent neurais networks for forecasting the energy consumption in buildings of a public institution in the state of Espírito Santo. In this work, climatic variables such as temperature, humidity, among others, from different regions where these buildings are located will be considered. The results presented by the LSTM were quite satisfactory, especially considering this is an initial research study.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Predictability of Energy Consumption in a Public Institution Using ANN

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Marcio Greick Pereira Brito,
  • Renner Sartório Camargo,
  • Gustavo Maia de Almeida

摘要

This paper presents an application of Long Short-Term Memory (LSTM) recurrent neurais networks for forecasting the energy consumption in buildings of a public institution in the state of Espírito Santo. In this work, climatic variables such as temperature, humidity, among others, from different regions where these buildings are located will be considered. The results presented by the LSTM were quite satisfactory, especially considering this is an initial research study.