{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T07:08:35Z","timestamp":1777705715567,"version":"3.51.4"},"reference-count":32,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2023,2,7]],"date-time":"2023-02-07T00:00:00Z","timestamp":1675728000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems: Applications in Engineering and Technology"],"published-print":{"date-parts":[[2023,5,4]]},"abstract":"<jats:p>Blast-induced ground vibration is highly possible to result in serious losses such as destroyed buildings. The crucial parameter of the mentioned vibration is peak particle velocity (PPV). Many equations have been developed to predict PPV, however, worse performance has been reported by multiple literatures. This paper developed a method for predicting PPV based on Mamdani Fuzzy Inference System. Firstly, Minimum Redundancy Maximum Relevance was employed to identify the blasting design parameters which significantly contribute to the PPV induced by blasting. Secondly, K-means method was applied to determine the value ranges of the selected parameters. The selected parameters and corresponding value ranges were combined to input into Mamdani Fuzzy Inference System for obtaining predicted PPV. Totally, 280 samples were collected from a blasting site. 260 out of them were used to train the proposed method and 20 were assigned for test. The proposed method was tested in the comparison with empirical equation USBM, multiple linear regression analysis, pure Mamdani Fuzzy Inference System in terms of the difference between predicted PPV and measured PPV, coefficient of correlation, root-mean-square error, and mean absolute error. The results from that showed that the proposed method has the better performance in PPV prediction.<\/jats:p>","DOI":"10.3233\/jifs-223195","type":"journal-article","created":{"date-parts":[[2023,2,10]],"date-time":"2023-02-10T12:42:56Z","timestamp":1676032976000},"page":"7513-7522","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["A method for predicting blast-induced ground vibration based on Mamdani Fuzzy Inference System"],"prefix":"10.1177","volume":"44","author":[{"given":"Yong","family":"Chen","sequence":"first","affiliation":[{"name":"China Construction Third Engineering BureauInfrastructure Construction Investment Co., LTD, Wuhan, PR China"}]},{"given":"Feiyu","family":"Long","sequence":"additional","affiliation":[{"name":"China Construction Third Engineering BureauInfrastructure Construction Investment Co., LTD, Wuhan, PR China"}]},{"given":"Wei","family":"Kuang","sequence":"additional","affiliation":[{"name":"China Construction Third Engineering BureauInfrastructure Construction Investment Co., LTD, Wuhan, PR China"}]},{"given":"Tianbao","family":"Zhang","sequence":"additional","affiliation":[{"name":"China Construction Third Engineering BureauInfrastructure Construction Investment Co., LTD, Wuhan, PR China"}]}],"member":"179","published-online":{"date-parts":[[2023,2,7]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10706-004-7068-x"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.17159\/2411-9717\/2016\/v116n5a7"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrmms.2009.03.004"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00366-018-0578-6"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1007\/s13762-016-0979-2"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrmms.2010.08.005"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00366-018-0659-6"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.soildyn.2011.04.004"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jafrearsci.2018.05.004"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12517-015-1908-2"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10230-007-0157-3"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00366-018-0686-3"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12517-021-08620-z"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrmms.2018.01.038"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ssci.2009.10.009"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00366-017-0546-6"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1177\/1077546319829938"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.soildyn.2020.106390"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1177\/1077546312437002"},{"key":"e_1_3_2_21_2","first-page":"1","article-title":"Prediction of a Blast Induced Peak Particle Velocity in Mining Operations: A Fuzzy Mamdani and ANFIS-Based Evaluating Methodology","volume":"1","author":"Machesa M.","year":"2021","unstructured":"Machesa, M., Tartibu, L.K., Okwu, M.O., Prediction of a Blast Induced Peak Particle Velocity in Mining Operations: A Fuzzy Mamdani and ANFIS-Based Evaluating Methodology, Proceedings of the ASME 2021 International Mechanical Engineering Congress and Exposition 1 (2021), 1\u20139.","journal-title":"Proceedings of the ASME 2021 International Mechanical Engineering Congress and Exposition"},{"key":"e_1_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.1007\/s40815-017-0378-y"},{"key":"e_1_3_2_23_2","doi-asserted-by":"crossref","unstructured":"Chai Y.Y. 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