热管开发地热能综合利用系统预测数据集

热管开发地热能综合利用智能控制平台数据集主要面向地热能综合利用系统设计、优化研究及系统实际应用的可靠数据支撑需求建设，基于热管开发地热能系统真实运行采集数据（在数据预处理中，通过剔除异常值、填补缺失值等方法确保了数据的完整性与一致性）及 Python 实现的神经网络训练模型（经多轮训练验证、权重参数优化以捕捉系统非线性关系）产生，主要记录了热管温度、热管压力、热管工质流量及不同运行条件下系统的性能参数等。This dataset was developed to offer reliable data support for the design, optimization research, and practical deployment of comprehensive geothermal energy utilization systems. It is generated from two core sources: real operational data collected from heat pipe-based geothermal energy systems (with data integrity and consistency guaranteed through preprocessing steps such as outlier removal and missing value imputation) and Python-implemented neural network training models, which have undergone multiple rounds of training validation and weight parameter optimization to capture the nonlinear inherent relationships of the system. The dataset primarily records parameters including heat pipe temperature, heat pipe pressure, heat pipe working fluid flow rate, and system performance metrics under diverse operating conditions.

搜集汇总

背景与挑战

背景概述

该数据集面向地热能综合利用系统的设计、优化研究及实际应用需求，提供可靠数据支撑。它基于热管开发地热能系统的真实运行数据，经过预处理确保完整性和一致性，并通过Python神经网络训练模型生成，记录了热管温度、压力、工质流量及系统性能参数等关键信息。