SIMULATION OF ACOUSTIC PRODUCT PROPERTIES IN VIRTUAL ENVIRONMENTS BASED ON ARTIFICIAL NEURAL NETWORKS (ANN)

被引：0

作者：

Siegel, Antje ^{[1
]}

Weber, Christian ^{[1
]}

Albers, Albert ^{[2
]}

Landes, David ^{[2
]}

Behrendt, Matthias ^{[2
]}

机构：

[1] Tech Univ Ilmenau, Ilmenau, Germany

[2] Karlsruhe Inst Technol KIT, Karlsruhe, Germany

来源：

DS87-4 PROCEEDINGS OF THE 21ST INTERNATIONAL CONFERENCE ON ENGINEERING DESIGN (ICED 17), VOL 4: DESIGN METHODS AND TOOLS | 2017年

关键词：

Virtual Engineering (VE); Simulation; Design informatics; Artificial neural networks; Acoustic product properties;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Acoustic product properties are playing an increasingly important role for product developers and designers. At the one hand the sound of a product has influence on the buying behavior of customers and on the other hand manufacturers have to meet many regulations and standards regarding the sound emissions of their products. Limits for these sound emissions are defined in order to protect humans and the animal world from noise pollution. The paper deals with a concept for acoustic simulation in virtual environments so that the acoustic properties of products can be studied. The concept is based on artificial neural networks (ANNs) which are applicable for many different tasks. With help of the virtual acoustic simulation the acoustic behavior of products or of individual product components can be validated during the whole product development process. In this way, noise pollution can be reduced and a higher compatibility with human health and environment can be reached.

引用

页码：573 / 582

页数：10

共 50 条

[1] ANN*: A Heuristic Search Algorithm Based on Artificial Neural Networks
Li, Guangli
Wang, Guancheng
Wang, Qiang
Fei, Fan
Lu, Shuai
Guo, Degui
PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATION PROCESSING (ICIIP'16), 2016,
[2] Virtual teaching and learning environments: automatic evaluation with artificial neural networks
Lino, Adriano
Rocha, Alvaro
Sizo, Amanda
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2019, 22 (Suppl 3): : S7217 - S7227
[3] Virtual teaching and learning environments: automatic evaluation with artificial neural networks
Adriano Lino
Álvaro Rocha
Amanda Sizo
Cluster Computing, 2019, 22 : 7217 - 7227
[4] IDENTIFICATION AND SIMULATION MODELS OF OPERATING SYSTEMS BASED ON ARTIFICIAL NEURAL NETWORKS
Valcic, Marko
Skenderovic, Julije
POMORSTVO-SCIENTIFIC JOURNAL OF MARITIME RESEARCH, 2005, 19 (01) : 43 - 64
[5] Artificial Neural Network (ANN) Based Modeling for Karstic Groundwater Level Simulation
Ioannis C. Trichakis
Ioannis K. Nikolos
G. P. Karatzas
Water Resources Management, 2011, 25 : 1143 - 1152
[6] Artificial Neural Network (ANN) Based Modeling for Karstic Groundwater Level Simulation
Trichakis, Ioannis C.
Nikolos, Ioannis K.
Karatzas, G. P.
WATER RESOURCES MANAGEMENT, 2011, 25 (04) : 1143 - 1152
[7] Simulation metamodeling through artificial neural networks
Fonseca, DJ
Navaresse, DO
Moynihan, GP
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2003, 16 (03) : 177 - 183
[8] Coupling simulation with artificial neural networks for the optimisation of HVAC controls in manufacturing environments
Mawson, Victoria Jayne
Hughes, Ben Richard
OPTIMIZATION AND ENGINEERING, 2021, 22 (01) : 103 - 119
[9] Coupling simulation with artificial neural networks for the optimisation of HVAC controls in manufacturing environments
Victoria Jayne Mawson
Ben Richard Hughes
Optimization and Engineering, 2021, 22 : 103 - 119
[10] Development of a dynamic surface roughness monitoring system based on artificial neural networks (ANN) in milling operation
Khorasani, AmirMahyar
Yazdi, Mohammad Reza Soleymani
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2017, 93 (1-4) : 141 - 151

← 1 2 3 4 5 →