Optimization of the heat recovery performance of enhanced geothermal system based on PSO-GA-BP neural networks and analytic hierarchy process
Abstract Numerical simulation is the most commonly used method to predict the power generation capacity of EGS during geothermal energy extraction. However, it is time-consuming to optimize the scheme only by comparing the numerical simulation methods, and it is difficult to determine the globally o...
Saved in:
| Main Authors: | Ling Zhou, Jingchao Sun, Yanjun Zhang, Yunjuan Chen, Honglei Lei |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-07509-1 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An Intelligent Optimization System Using Neural Networks and Soft Computing for the FMM Etching Process
by: Wen-Chin Chen, et al.
Published: (2025-06-01) -
Construction of teaching quality evaluation model of online dance teaching course based on improved PSO-BPNN
by: Jin Ben, et al.
Published: (2025-05-01) -
Quantitative evaluation system of geothermal resources based on analytic hierarchy process: A case study of middle-deep hydrothermal sandstone reservoir in Caofeidian of Hebei Province
by: HE Dongbo, REN Lu, HAO Jie, LIU Xiaoping, CAO Qian
Published: (2023-12-01) -
Identification of Sarin Simulant DMMP Based on a Laminated MOS Sensor Using Article Swarm Optimization-Backpropagation Neural Network
by: Ting Liang, et al.
Published: (2025-04-01) -
Feature Importance Analysis for Compressive Bearing Capacity of HSCM Piles Based on GA-BPNN
by: Fangzhou Chu, et al.
Published: (2025-08-01)