The invention discloses an intelligent building personalized
space management method based on a deep neural network, and the method comprises the following steps: S1, collecting environment parameters, user behaviors and
preference data, and constructing personalized control input; s2, cleaning, aligning, normalizing and missing filling are performed on the acquired data, and a standardized
data set is generated; s3, constructing a deep neural
network model, and predicting personalized
control parameters; s4, inputting a prediction result into a
whale optimization
algorithm, and generating a control strategy candidate set meeting comfort and
energy consumption targets; s5, inputting the candidate strategy to a water wave optimization
algorithm, fusing multi-user preferences, and outputting a final control strategy; s6, a control instruction is issued to the building
system, and environment adjustment is executed; and S7, collecting adjustment feedback, calculating an error and updating the neural
network model to realize
continuous optimization. According to the invention, intelligent regulation and control and personalized optimization of the building
space environment are realized, and the comfort level and the energy efficiency
management level are remarkably improved.