Data Enrichment and Increment for Deep Learning Component-based Energy Prediction Model

This dataset is used for training of deep learning (DL) component based machine learning models described in the linked article. The article examines the effect of enriching training data with several building shapes on the prediction accuracy of machine learning models. There are nine building shapes used to collect the training data using EnergyPlus. Please read the full article for the relevant details of component structure and training of DL components. There are seven training dataset BaseCase, E-1, E-2, E-3, I-1, I-2, and I-3 and one test dataset TestData. The trained DL component are saved under Models folder in each dataset. The performance.csv file inside each dataset folder describes the performance of DL components trained on the corresponding dataset.本数据集用于训练本文所附文章中所述的基于深度学习（Deep Learning, DL）组件的机器学习模型。该文章探讨了通过引入多种建筑形状扩充训练数据对机器学习模型预测精度的影响。本次研究采用EnergyPlus软件，基于9种建筑形状采集训练数据。如需了解组件结构及深度学习组件训练的相关细节，请参阅完整原文。本次数据集包含7个训练数据集（BaseCase、E-1、E-2、E-3、I-1、I-2、I-3）以及1个测试数据集TestData。训练完成的深度学习组件将被保存至各数据集目录下的Models文件夹中。各数据集目录内的performance.csv文件，记录了基于对应数据集训练的深度学习组件的性能表现。