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（1）
Analysis of public and industrial building area data of China based on Taylor-series neural network method (1)
摘要：
依据竣工面积与用地面积、建筑面积与用地面积之间的关系，采用泰勒级数神经网络方法计算了2001—2006年逐年公共建筑、工业建筑面积。在此基础上分析了国内生产总值、第三产业增加值、就业人数对公共建筑、工业建筑面积的影响。
关键词：公共建筑,工业建筑,统计年鉴,时间序列,泰勒级数,神经网络,建筑能耗
Abstract：
Based on the relationship between the completed area and the land area, as well as the construction area and the land area, uses the Taylor-series neural network method to calculate the annual public and industrial building area from 2001 to 2014. On this basis, analyses the influence of the gross domestic product (GDP), the added value of tertiary industry and the number of employed persons on public and industrial building area.
Keywords:public building, industrial building, statistical yearbook, time series, Taylor-series, neural network, building energy consumption