An Airport Noise Prediction Model Based on Selective Ensemble of LOF-FSVR

Author(s):  
Haiyan Chen ◽  
Jiajia Deng ◽  
Bo Sun ◽  
Jiandong Wang
2014 ◽  
Vol 986-987 ◽  
pp. 1356-1359
Author(s):  
You Xian Peng ◽  
Bo Tang ◽  
Hong Ying Cao ◽  
Bin Chen ◽  
Yu Li

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.


2017 ◽  
Vol 143 (6) ◽  
pp. 04017008 ◽  
Author(s):  
Nahyun Kwon ◽  
Moonseo Park ◽  
Hyun-Soo Lee ◽  
Joseph Ahn ◽  
Sooyoung Kim

2013 ◽  
Vol 409-410 ◽  
pp. 688-694
Author(s):  
Li Na Cao ◽  
Wei Sheng Guan

In this paper, an improved noise prediction model based on FHWA was used in the noise prediction and evaluation of Shang Zhou to Dan Feng expressway to study the function of the model playing in environmental impact assessment.


2012 ◽  
Vol 3 (4) ◽  
pp. 110-112
Author(s):  
Rahul Singh ◽  
◽  
Parveen Bawa ◽  
Ranjan Kumar Thakur

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