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房间辐射时间序列决策树分类方法研究
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Research on Decision Tree Classification Method for Room Radiation Time Series
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    摘要:

    采用辐射时间序列方法,现有可用的辐射时间序列涉及的房间结构和特征参数数量太少,导致其计算的空调设计负荷偏差较大. 考虑国内建筑常用的围护结构及其特征参数,采用简单随机抽样方法抽取结构和特征参数组合的房间样本,应用热平衡方法计算大量的结构与特征组合房间样本的辐射时间序列,用CART决策树算法提取影响房间辐射时间序列的主要特征参数,对房间结构类型和特征参数进行分类,用K-Medoids中心算法确定各类房间代表性辐射时间序列. 用提出的决策树分类方法将结构及其特性参数组合房间的非太阳辐射时间序列和太阳辐射时间序列分别分为12类和8类. 适用性检验表明,分类后每类房间辐射时间序列很好地代表了该类的所有房间,可显著提高空调设计负荷的准确性.

    Abstract:

    The available radiation time series employing the radiation time series method involves too few room structures and characteristic parameter numbers, which results in a large deviation of the design cooling load. Firstly, considering the commonly-used envelop structures and their characteristic parameters of buildings in China, the room samples combined with the structures and their characteristic parameters were sampled by a simple random method. Then, the heat balance method was used to calculate the radiation time series of each room sample. The main characteristic parameters that affect the radiation time series of a room are extracted by the CART algorithm, and the rooms were classified according to the main characteristic parameters. Finally, the K-Medoids algorithm is used to determine the representative radiation time series for each type of room. Using the proposed decision tree classification method, the non-solar radiation time series and the solar radiation time series of all rooms combined by the structures and their characteristic parameters were classified into twelve and eight categories, respectively. The applicability verification shows that the representative radiation time series for each category of rooms well represents all rooms in this category, which can significantly improve the accuracy of design cooling load.

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陈友明 ?,刘佳明 ,宁柏松 ,方政诚 .房间辐射时间序列决策树分类方法研究[J].湖南大学学报:自然科学版,2023,(5):223~230

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  • 在线发布日期: 2023-06-05
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