Performance prediction of a ground source heat pump system using denoised long short-term memory neural network optimised by fast non-dominated sorting genetic algorithm-II-Reference-Cited by-同舟云学术

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Performance prediction of a ground source heat pump system using denoised long short-term memory neural network optimised by fast non-dominated sorting genetic algorithm-II

Published:2024-06 Issue: Volume:120 Page:103002
ISSN:0375-6505
Container-title:Geothermics
language:en
Short-container-title:Geothermics

Author:

Chaoran Wang,Xiong (Bill) Yu,Chanjuan Han^ORCID

Publisher

Elsevier BV

Reference63 articles.

1. Field study of heating performance of three ground-source heat pumps in Canadian single-family houses;Abdel-Salam;Energy Build.,2021

2. On the impact of outlier filtering on the electricity price forecasting accuracy;Afanasyev;Appl. Energy,2019

3. Assessing the impact of borehole field data on AI-based deep learning models for heating and cooling prediction;Ahmed;Geothermics,2024

4. Automated deep reinforcement learning for real-time scheduling strategy of multi-energy system integrated with post-carbon and direct-air carbon captured system;Alabi;Appl. Energy,2023

5. Real-time energy optimization and scheduling of buildings integrated with renewable microgrid;Alzahrani;Appl. Energy,2023

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Operational strategy optimization of an existing ground source heat pump (GSHP) system using an XGBoost surrogate model;Energy and Buildings;2024-09

2. Experimental and numerical investigations on thermo-mechanical behaviors of energy pile group under different operational strategies;Geothermics;2024-09

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