Study on configuration sequence of indemnificatory community public service facility based on MIV-BP Neural Network

Tianyan Wu, Jianjun Zhan, Wei Yan 

School of Urban Construction and Safety engineering, Shanghai Institute of Technology, Shanghai, China

China is seeing large-scale construction of indemnificatory community being. Yet due to lack of dynamic planning and arrangement in advance and little consideration of public service facility configuration sequence, the configuration of public service facility in indemnificatory community is lagging behind and inefficient, failing to attract the residents to move in the community. This paper structures the MIV-BP Neural Network Model, and gives an empirical analysis on the influence sequence of the indemnificatory community public service facilities to the population occupancy rate. The results suggest that the configuration of public service facility in indemnificatory community should be sequentially configured in period and in grade according to the community’s specific present situation and developmental conditions as well as the continuous increase of population occupancy rate.