【摘要】 面对日趋严重的人口老龄化问题，高层住宅中适老化改造需求提上了议事日程。在分析既往相关研究和参考专家意见的基础上，建立了高层住宅适老化改造需求预测的指标体系，并选取Back Propagation（简称BP）人工神经网络预测模型。通过对某中心城市多个居住区高层住宅空间及环境进行实地踏勘和问卷调查，将收集的数据处理后分别导入BP人工神经模型中进行训练，通过参数寻优进一步优化预测效果，为今后高层住宅适老化改造设计的实施提供理论依据。更多还原

【Abstract】 Based on the analysis of previous relevant research and reference to expert opinions, an indicator system for predicting the demand for aging friendly renovation of high-rise residential buildings has been established. By selecting a BP artificial neural network prediction model, conducting on-site surveys and questionnaire surveys on the space and environment of high-rise residential buildings in multiple residential areas in a central city, and processing the collected data before importing them into the BP artificial neural model for training, further optimizing the prediction effect through parameter optimization, this work provides a solid theoretical basis for the implementation of aging resistant renovation design of high-rise residential buildings in the future.更多还原