Dataset for "Transient Resonant Peak Sequencing for Multiple-Leaks Localization: A Novel Graphical Framework"

This dataset contains all the data for the article titled "Transient Resonant Peak Sequencing for Multiple-Leaks Localization: A Novel Graphical Framework". There has been a minor change in Figure ordering in the article. Figure 3a and Figure 3b refers to the FRF of the system with a single leak with xL/L = 0.1 and 0.14. Figure 12 a,b,c,d refers to the FRF of the system with two leaks denoted as validation case 1,2,3,4 with the leak ratio of 1.0.  Figure 14 a,b,c,d refers to the FRF of the system with two leaks denoted as case 1,2,3,4 with the leak ratio of 0.8. Figure 16 a,b,c,d refers to the FRF of the system with two leaks denoted as case 1,2,3,4 with the leak ratio of 0.6.In the updated version, the following information are added:Validation where the leak ratio is 0.2 and 0.4Combined order table with the ratio of 0.2 and 0.4Distance ratio 0.2 and 0.4: The distance between the true leak locations with the closest bound of leak subdomainSensitivity result summary: Shows the summary of method's performance when the noisy data is consideredSensitivity case 1 realization 0: Example of noisy data used for suggesting alternative to the method in the existence of noiseCombined order table with ratio 1.0 sens: This is the combined order table assuming only four measurement points are consideredCombined metrics noisy / noiseless classification: This is the summary of recall, precision, and F1 score of different class for CatBoost model based on noiseless and noisy dataConfusion matrix noisy / noiseless classification: This is the confusion matrix of the CatBoost model based on noiseless and noisy dataRegression data ML: This is the result of regression based on CatBoost model given the leak locations are directly addedComparison_ITA_instance: The pkl file for ITA training instance