Abstract. This paper aims to summarize the findings of research concerning the application of neural networks in traffic noise prediction. Modeling and prediction of traffic noise by means of classical approaches is a very complex and nonlinear process, due to involvement of several factors on which noise level depends. To overcome these problems, researchers and acoustical engineers have applied the artificial neural network in the field of traffic noise prediction. After a critical review of various neural network based models developed for road traffic noise prediction cited in the literature it was concluded that ANN based models were capable of predicting traffic noise more accurately and effectively as compared to deterministic and st...
The dangerous effect of noise on human health is well known. Both the auditory and non-auditory effe...
Vehicular traffic plays a significant role in terms of economic development; however, it is also a m...
Traffic noise can be classified among the worst factors in terms of damage to people’s health and we...
This paper aims to summarize the findings of research concerning the application of neural networks ...
This research has been motivated by the fact that present road traffic noise prediction models have...
xiii, 109 leaves : illustrations ; 30 cmPolyU Library Call No.: [THS] LG51 .H577M BSE 2014 ChuNoise ...
In the issue of expanding noise levels the world over, road traffic noise is main contributor. The i...
Noise is a sound of variable frequencies considered as one of the leading causes of environmental ...
© 2016 Acoustical Society of America. Available traffic noise prediction models are usually based on...
Noise is a global problem. In 1972 the World Health Organization (WHO) classified noise as a polluta...
Noise is a global problem. In 1972 the World Health Organization (WHO) classified noise as apollutan...
© 2019, Springer Nature Switzerland AG. This study proposes a neural network (NN) model to predict a...
Jaen is a city in constant urban growth which generates an increase in vehicular traffic and active ...
Over the last decades, the number of motor vehicles has increased dramatically in Iran, where differ...
A vehicular road traffic noise prediction methodology based on machine learning techniques has been ...
The dangerous effect of noise on human health is well known. Both the auditory and non-auditory effe...
Vehicular traffic plays a significant role in terms of economic development; however, it is also a m...
Traffic noise can be classified among the worst factors in terms of damage to people’s health and we...
This paper aims to summarize the findings of research concerning the application of neural networks ...
This research has been motivated by the fact that present road traffic noise prediction models have...
xiii, 109 leaves : illustrations ; 30 cmPolyU Library Call No.: [THS] LG51 .H577M BSE 2014 ChuNoise ...
In the issue of expanding noise levels the world over, road traffic noise is main contributor. The i...
Noise is a sound of variable frequencies considered as one of the leading causes of environmental ...
© 2016 Acoustical Society of America. Available traffic noise prediction models are usually based on...
Noise is a global problem. In 1972 the World Health Organization (WHO) classified noise as a polluta...
Noise is a global problem. In 1972 the World Health Organization (WHO) classified noise as apollutan...
© 2019, Springer Nature Switzerland AG. This study proposes a neural network (NN) model to predict a...
Jaen is a city in constant urban growth which generates an increase in vehicular traffic and active ...
Over the last decades, the number of motor vehicles has increased dramatically in Iran, where differ...
A vehicular road traffic noise prediction methodology based on machine learning techniques has been ...
The dangerous effect of noise on human health is well known. Both the auditory and non-auditory effe...
Vehicular traffic plays a significant role in terms of economic development; however, it is also a m...
Traffic noise can be classified among the worst factors in terms of damage to people’s health and we...