ORIGINAL RESEARCH
Prediction and Evaluation of Park Sound Comfort
Based on Back Propagation Neural Network
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School of Architecture, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
Submission date: 2022-04-26
Final revision date: 2022-05-16
Acceptance date: 2022-05-24
Online publication date: 2022-08-02
Publication date: 2022-09-28
Corresponding author
Qindong Fan
North China University of Water Resources and Electric Power, China
Pol. J. Environ. Stud. 2022;31(5):4623-4639
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ABSTRACT
Park soundscape construction is an important method to improve the quality of urban environments.
At present, the studies on soundscape mostly focus on the evaluation of soundscape indexes
and the accuracy analysis of model simulations of actual sites, but the research on small-scale
soundscape characteristic spaces is inadequate. Based on a Back Propagation(BP) neural network model,
we predict and evaluate the sound comfort in a park. The results show that: (1) The distribution trends of
measured and predicted sound comfort values in different scenes (space type, plant type, functional area
and sound source type) are relatively consistent. (2) A sound comfort of the park is space dependent.
The sound landscape design of small-scale characteristic space is of great significance to improve
the environmental quality. (3) The evaluation of emotional acoustics has obvious correlation with
sound comfort. (4) The soundscape planning process based on BP neural network is clearly proposed.
The research results are of great significance to promote soundscape evaluation and planning based
on the evaluation results.