Prediction of soil temperatures for shallow geothermal applications in Turkey
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DOI: 10.1016/j.rser.2016.11.065
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Cited by:
- Sung-Woo Cho & Pyeongchan Ihm, 2018. "Development of a Simplified Regression Equation for Predicting Underground Temperature Distributions in Korea," Energies, MDPI, vol. 11(11), pages 1-18, October.
- Mohammad Taghi Sattari & Anca Avram & Halit Apaydin & Oliviu Matei, 2020. "Soil Temperature Estimation with Meteorological Parameters by Using Tree-Based Hybrid Data Mining Models," Mathematics, MDPI, vol. 8(9), pages 1-21, August.
- Xing, Lu & Li, Liheng & Gong, Jiakang & Ren, Chen & Liu, Jiangyan & Chen, Huanxin, 2018. "Daily soil temperatures predictions for various climates in United States using data-driven model," Energy, Elsevier, vol. 160(C), pages 430-440.
- Zhang, Guanshan & Ding, Xiaoming & Li, Tianhua & Pu, Wenyang & Lou, Wei & Hou, Jialin, 2020. "Dynamic energy balance model of a glass greenhouse: An experimental validation and solar energy analysis," Energy, Elsevier, vol. 198(C).
- Cai, Wanlong & Wang, Fenghao & Chen, Chaofan & Chen, Shuang & Liu, Jun & Ren, Zhanli & Shao, Haibing, 2022. "Long-term performance evaluation for deep borehole heat exchanger array under different soil thermal properties and system layouts," Energy, Elsevier, vol. 241(C).
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Keywords
Soil temperature; Renewable energy; Geothermal energy; Temperature variations; Energy efficiency; Shallow depth geothermal resources;All these keywords.
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