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能源效率数据集,12种不同建筑物形状进行能量分析

能源效率数据集,12种不同建筑物形状进行能量分析

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Computer Classification

Data Set Information:We perform energy analysis using 12 different building shapes simulated in Ecotect. The buildings d......

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    README.md

    Data Set Information:

    We perform energy analysis using 12 different building shapes simulated in Ecotect. The buildings differ with respect to the glazing area, the glazing area distribution, and the orientation, amongst other parameters. We simulate various settings as functions of the afore-mentioned characteristics to obtain 768 building shapes. The dataset comprises 768 samples and 8 features, aiming to predict two real valued responses. It can also be used as a multi-class classification problem if the response is rounded to the nearest integer.


    Attribute Information:

    The dataset contains eight attributes (or features, denoted by X1...X8) and two responses (or outcomes, denoted by y1 and y2). The aim is to use the eight features to predict each of the two responses.

    Specifically:
    X1 Relative Compactness
    X2 Surface Area
    X3 Wall Area
    X4 Roof Area
    X5 Overall Height
    X6 Orientation
    X7 Glazing Area
    X8 Glazing Area Distribution
    y1 Heating Load
    y2 Cooling Load


    Relevant Papers:

    A. Tsanas, A. Xifara: 'Accurate quantitative estimation of energy performance of residential buildings using statistical machine learning tools', Energy and Buildings, Vol. 49, pp. 560-567, 2012


    Citation Request:

    A. Tsanas, A. Xifara: 'Accurate quantitative estimation of energy performance of residential buildings using statistical machine learning tools', Energy and Buildings, Vol. 49, pp. 560-567, 2012 (the paper can be accessed from [Web link])

    For further details on the data analysis methodology:
    A. Tsanas, 'Accurate telemonitoring of Parkinsona€?s disease symptom severity using nonlinear speech signal processing and statistical machine learning', D.Phil. thesis, University of Oxford, 2012 (which can be accessed from [Web link])


    The dataset was created by Angeliki Xifara (angxifara '@' gmail.com, Civil/Structural Engineer) and was processed by Athanasios Tsanas (tsanasthanasis '@' gmail.com, Oxford Centre for Industrial and Applied Mathematics, University of Oxford, UK).

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