Abstract
The study conducts time-series approach for analysing one year noise monitoring data. Support vector machine (SVM) technique is used as a modelling technique for time-series approach. The noise data is trained using tenfold cross-validation to get optimum hyperparameters (γ, ε, C). The performance and accuracy of model are determined by statistical parameters like MSE, RMSE, MAPE in %, R2. The paper predicts an error of ±2 dB(A) with the implementation of support vector machine (SVM).
