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This study proposes an innovative IHO-VMD-CatBoost model that integrates variational mode decomposition (VMD) and the CatBoost algorithm, with hyperparameters globally optimized using the improved hippopotamus optimization (IHO) algorithm. Compared to existing models, the proposed method improves feature extraction from vibration signals and significantly enhances prediction accuracy, especially in complex geological conditions. Using measured data from open-pit mine blasting, the model extracts key features such as maximum section charge, total charge, and horizontal distance, achieving superior performance compared to 13 traditional models. It reports a root mean square error of 0.28 cm\/s, a mean absolute error of 0.17 cm\/s, an index of agreement of 0.993, and a variance accounted for value of 97.28%, demonstrating superior prediction accuracy, a high degree of fit with observed data, and overall robustness in PPV prediction. Additionally, analyses based on the SHapley Additive Explanations framework provide insights into the complex nonlinear relationships between factors like horizontal distance and maximum section charge, improving the model\u2019s interpretability. The model demonstrates robustness, stability, and applicability in various tests, confirming its reliability in complex engineering scenarios, and offering a valuable solution for safe mining and optimized blasting design.<\/jats:p>","DOI":"10.1093\/jcde\/qwaf007","type":"journal-article","created":{"date-parts":[[2025,1,17]],"date-time":"2025-01-17T05:21:24Z","timestamp":1737091284000},"page":"154-176","source":"Crossref","is-referenced-by-count":6,"title":["Assessment of peak particle velocity of blast vibration using hybrid soft computing approaches"],"prefix":"10.1093","volume":"12","author":[{"given":"Haiping","family":"Yuan","sequence":"first","affiliation":[{"name":"College of Civil Engineering, Hefei University of Technology , Hefei 230009 ,","place":["China"]},{"name":"State Key Laboratory of Mining \u223c Induced Response and Disaster Prevention Control in Deep Coal Mines , Huainan 232001 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