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Geoscience ›› 2023, Vol. 37 ›› Issue (04): 963-971.DOI: 10.19657/j.geoscience.1000-8527.2021.063

• Water Resources and Environmental Geology • Previous Articles     Next Articles

Suitability Zoning for Groundwater Source Heat Pump Based on Adaptive BPNN-GIS Method

YAN Baizhong1,2(), SUN Jian1,2,3, CHEN Jiaqi1,2, SUN Fengbo1,2, LI Xiaomeng1,2, FU Qingjie4   

  1. 1. School of Water Resources & Environment, Hebei Center for Ecological and Environmental Geology Research, Hebei GEO University, Shijiazhuang, Hebei 050031, China
    2. Hebei Key Laboratory of Geological Resources and Environment Monitoring and Protection, Shijiazhuang, Hebei 050031, China
    3. Zhejiang Geological Prospecting Institute of CCGMB, Hangzhou, Zhejiang 311201, China
    4. Shandong Provincial Lunan Geology and Exploration Institute (No.2 Geological Brigade of the Shandong BGMR), Shandong Provincial Engineering Research Center of Geothermal Energy Exploration and Development, Jining, Shandong 272100, China
  • Received:2020-11-16 Revised:2023-01-25 Online:2023-08-10 Published:2023-09-02

Abstract:

Based on the geological and hydrogeological conditions of Shijiazhuang City, the suitability evaluation index system of groundwater source heat pump is established. The adaptive BP neural network and GIS coupling method were used to evaluate the suitability of groundwater source heat pump, and the results were compared with the fuzzy analytic hierarchy process. The results show that in addition to the difference in the area, the suitability distribution of the two methods is basically the same. The proportion difference of the suitable area between the BP neural network and fuzzy analytic hierarchy process is only 3.80%, 8.06%, and 11.86%, respectively. The self-adaptive BPNN-GIS evaluation method could resolve the drawbacks of traditional manual adjustment and subjective weighting. Meanwhile, both the evaluation efficiency and accuracy are higher, which can reflect the degree of single point suitability in the study area.

Key words: groundwater source heat pump, BP neural network, suitability area, Shijiazhuang

CLC Number: