Environmental Assessment Model of Green Ecological Residential Buildings Based on Bayesian Network

Dongmei Li, Dehua Jia

Ekoloji, 2019, Issue 108, Pages: 587-592


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Aiming at the problems of low accuracy and long time-consuming in the existing green ecological residential building environment assessment model, a green ecological residential building environment assessment model based on Bayesian network is proposed. Based on the analysis of the four basic characteristics of green ecological residential buildings, the environmental assessment model of green ecological residential buildings is constructed by using Bayesian network. The concrete implementation steps include structure learning, parameter learning and reasoning calculation. For structure learning, expert construction is used to determine the Bayesian network node, and then construct causal topology structure, including initial network and transfer network. For parameter learning, EM algorithm is used to train and learn discrete data sets to obtain the probability distribution of different nodes. The BN with known structure and parameters is reasoned and predicted, and given test data sets, the probability distribution of different nodes is obtained. The probabilistic distributions of different time nodes are used to obtain the environmental assessment results of green ecological residential buildings. The experimental results show that the evaluation accuracy of the model is high and the time-consuming is low, which indicates that the model is feasible.


Bayesian network, green ecological housing, building environment, assessment model


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