基于泰勒级数神经网络方法的我国公共建筑和工业建筑面积数据分析（2）
Analysis of public and industrial building area data of China based on Taylor-series neural network method (2)
摘要：
系统梳理了我国统计年鉴中城镇和农村公共建筑、工业建筑面积的相关指标。采用泰勒级数神经网络方法计算了2001—2014年城镇公共建筑、工业建筑面积，采用线性拟合的方法得到了农村公共建筑面积，解决了统计年鉴中现有统计数据时间序列不完整、统计口径不一致的问题，为我国建筑能耗统计研究提供数据支撑。
关键词：建筑面积,公共建筑,工业建筑,时间序列,统计年鉴,建筑能耗
Abstract：
Systematically sorts the relevant indexes of urban and rural public and industrial building area in the statistical yearbooks of China. Calculates the urban public and industrial building area from 2001 to 2014 using the Taylor-series neural network method and obtains the rural public building area using the linear fitting method, which solves the problems of incomplete time series data and inconsistent statistical caliber in the existing statistical yearbook, providing data support for further study on building energy consumption statistic of China.
Keywords:building area, public building, industrial building, time series, statistical yearbook, building energy consumption