Hall building acoustic objective parameter prediction method and system based on machine learning
The invention discloses a hall building acoustic objective parameter prediction method and system based on machine learning. The method comprises the steps of obtaining to-be-predicted hall building ontology data and preprocessing the building ontology data to obtain hall building scalar data; and i...
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creator | YANG CHUNJIE DUAN JIWEI ZHANG HAIDING WEN JIE WAN YUPENG YANG RUI CHEN ZHENG |
description | The invention discloses a hall building acoustic objective parameter prediction method and system based on machine learning. The method comprises the steps of obtaining to-be-predicted hall building ontology data and preprocessing the building ontology data to obtain hall building scalar data; and inputting the scalar data of the hall building into a pre-established building acoustics objective parameter prediction model based on machine learning to obtain a prediction result of hall building acoustics objective parameters. According to the method, objective parameter indexes such as intermediate-frequency indoor reverberation time and language definition of the hall building are effectively predicted based on the prediction model established by machine learning, rapid evaluation of acoustic objective parameters of part of the hall building is realized, and the prediction precision of the acoustic objective parameters of the building is higher than that of a traditional method; manpower and material resources |
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The method comprises the steps of obtaining to-be-predicted hall building ontology data and preprocessing the building ontology data to obtain hall building scalar data; and inputting the scalar data of the hall building into a pre-established building acoustics objective parameter prediction model based on machine learning to obtain a prediction result of hall building acoustics objective parameters. 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The method comprises the steps of obtaining to-be-predicted hall building ontology data and preprocessing the building ontology data to obtain hall building scalar data; and inputting the scalar data of the hall building into a pre-established building acoustics objective parameter prediction model based on machine learning to obtain a prediction result of hall building acoustics objective parameters. According to the method, objective parameter indexes such as intermediate-frequency indoor reverberation time and language definition of the hall building are effectively predicted based on the prediction model established by machine learning, rapid evaluation of acoustic objective parameters of part of the hall building is realized, and the prediction precision of the acoustic objective parameters of the building is higher than that of a traditional method; manpower and material resources</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
title | Hall building acoustic objective parameter prediction method and system based on machine learning |
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