Multivariate Analysis of Passive Energy-Saving Design of High-Rise Residential Buildings Based on RBF and Orthogonal Test

The proportion of high-rise residential buildings in China is gradually increasing, and with the implementation of the national new green building evaluation standards and the continuous strengthening of energy conservation standards, the potential of passive energy saving needs to be further explored. Radial Basis Function (RBF) neural network and orthogonal experiment design range difference method were adopted for the nine passive influencing factors in the high-rise corridors in hot summer and cold winter regions. This research discusses the influence of different passive factors on the energy consumption of heating and cooling in high-rise residential buildings and the prioritization issues under the requirements of 50, 65 and 75% energy saving, to provide ideas and references for the passive energy-saving design of high-rise residential buildings.