A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Vehicular traffic noise prediction using soft computing approach
A new approach for the development of vehicular traffic noise prediction models is presented. Four different soft computing methods, namely, Generalized Linear Model, Decision Trees, Random Forests and Neural Networks, have been used to develop models to predict the hourly equivalent continuous sound pressure level, Leq, at different locations in the Patiala city in India. The input variables include the traffic volume per hour, percentage of heavy vehicles and average speed of vehicles. The performance of the four models is compared on the basis of performance criteria of coefficient of determination, mean square error and accuracy. 10-fold cross validation is done to check the stability of the Random Forest model, which gave the best results. A t-test is performed to check the fit of the model with the field data.
Vehicular traffic noise prediction using soft computing approach
A new approach for the development of vehicular traffic noise prediction models is presented. Four different soft computing methods, namely, Generalized Linear Model, Decision Trees, Random Forests and Neural Networks, have been used to develop models to predict the hourly equivalent continuous sound pressure level, Leq, at different locations in the Patiala city in India. The input variables include the traffic volume per hour, percentage of heavy vehicles and average speed of vehicles. The performance of the four models is compared on the basis of performance criteria of coefficient of determination, mean square error and accuracy. 10-fold cross validation is done to check the stability of the Random Forest model, which gave the best results. A t-test is performed to check the fit of the model with the field data.
Vehicular traffic noise prediction using soft computing approach
Singh, Daljeet (author) / Nigam, S P / Agrawal, V P / Kumar, Maneek
2016
Article (Journal)
English
BKL:
43.00
Soft computing approach to construction performance prediction and diagnosis
| British Library Online Contents | 2008
Soft computing approach to construction performance prediction and diagnosis
| Online Contents | 2008
Prediction of cement strength using soft computing techniques
| British Library Online Contents | 2004
Prediction of cement strength using soft computing techniques
| Online Contents | 2004