Experimental identification of a noise prediction model of a vibrating structure using optimal estimation techniques

1988 ◽  
Vol 84 (S1) ◽  
pp. S149-S149
Author(s):  
R. Aquilina ◽  
J. C. Flandrin ◽  
E. Gaud
Keyword(s):  
Prediction Model ◽  
Optimal Estimation ◽  
Noise Prediction ◽  
Estimation Techniques ◽  
Experimental Identification

Road Traffic Noise Prediction Model

2012 ◽  
Vol 3 (4) ◽  
pp. 110-112
Author(s):  
Rahul Singh ◽  
◽  
Parveen Bawa ◽  
Ranjan Kumar Thakur
Keyword(s):  
Prediction Model ◽  
Road Traffic ◽  
Traffic Noise ◽  
Road Traffic Noise ◽  
Noise Prediction

Traffic noise prediction model of an Indian road: an increased scenario of vehicles and honking

2020 ◽  
Vol 27 (30) ◽  
pp. 38311-38320
Author(s):  
Chaitanya Thakre ◽  
Vijaya Laxmi ◽  
Ritesh Vijay ◽  
Deepak J. Killedar ◽  
Rakesh Kumar
Keyword(s):  
Prediction Model ◽  
Traffic Noise ◽  
Noise Prediction

Road traffic noise prediction model in Thailand

1999 ◽  
Vol 58 (2) ◽  
pp. 123-130 ◽  
Author(s):  
Thanaphan Suksaard ◽  
Phaka Sukasem ◽  
S.Monthip Tabucanon ◽  
Ichiro Aoi ◽  
Kiyotsugu Shirai ◽  
...  
Keyword(s):  
Prediction Model ◽  
Road Traffic ◽  
Traffic Noise ◽  
Road Traffic Noise ◽  
Noise Prediction

A Model Based on BP Neural Network for Audible Noise Prediction

2014 ◽  
Vol 986-987 ◽  
pp. 1356-1359
Author(s):  
You Xian Peng ◽  
Bo Tang ◽  
Hong Ying Cao ◽  
Bin Chen ◽  
Yu Li
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Transmission Lines ◽  
Bp Neural Network ◽  
Prediction Models ◽  
Absolute Error ◽  
Research Area ◽  
Noise Prediction ◽  
Bp Network ◽  
Model Based

Audible noise prediction is a hot research area in power transmission engineering in recent years, especially come down to AC transmission lines. The conventional prediction models at present have got some problems such as big errors. In this paper, a prediction model is established based on BP network, in which the input variables are the four factors in the international common expression of power line audible noise and the noise value is the output. Take multiple measured power lines as an example, a train is made by the BP network and then the prediction model is set up in the hidden layer of the network. Using the trained model, the audible noise values are predicted. The final results show that the average absolute error in absolute terms of the values by the audible noise prediction model based on BP neural network is 1.6414 less than that predicted by the GE formula.

scholarly journals A semi-analytical noise prediction model for airfoils with serrated trailing edges

2019 ◽  
Vol 143 ◽  
pp. 679-691 ◽  
Author(s):  
Yannick D. Mayer ◽  
Benshuai Lyu ◽  
Hasan Kamliya Jawahar ◽  
Mahdi Azarpeyvand
Keyword(s):  
Prediction Model ◽  
Noise Prediction ◽  
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