{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T19:14:38Z","timestamp":1757618078807,"version":"3.44.0"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2025,5,31]],"date-time":"2025-05-31T00:00:00Z","timestamp":1748649600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,5,31]],"date-time":"2025-05-31T00:00:00Z","timestamp":1748649600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12302457"],"award-info":[{"award-number":["12302457"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Earth Sci Inform"],"published-print":{"date-parts":[[2025,6]]},"DOI":"10.1007\/s12145-025-01923-9","type":"journal-article","created":{"date-parts":[[2025,5,31]],"date-time":"2025-05-31T04:40:31Z","timestamp":1748666431000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Predicting the blast-induced ground vibration with support vector regression optimized by five swarm algorithms"],"prefix":"10.1007","volume":"18","author":[{"given":"Kai","family":"Rong","sequence":"first","affiliation":[]},{"given":"Xuan","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Haibo","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Jun","family":"Yang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,5,31]]},"reference":[{"key":"1923_CR1","doi-asserted-by":"publisher","first-page":"3335","DOI":"10.1007\/s00366-021-01444-1","volume":"38","author":"A Abbaszadeh Shahri","year":"2022","unstructured":"Abbaszadeh Shahri A, Pashamohammadi F, Asheghi R, Abbaszadeh Shahri H (2022) Automated intelligent hybrid computing schemes to predict blasting induced ground vibration. Eng Comput 38:3335\u20133349. https:\/\/doi.org\/10.1007\/s00366-021-01444-1","journal-title":"Eng Comput"},{"key":"1923_CR2","volume-title":"Rock mechanics in engineering practice","author":"NN Ambraseys","year":"1968","unstructured":"Ambraseys NN (1968) Rock mechanics in engineering practice. John Wiley & Sons, Incorporated"},{"key":"1923_CR3","doi-asserted-by":"publisher","first-page":"14681","DOI":"10.1007\/s00521-020-04822-w","volume":"32","author":"M Amiri","year":"2020","unstructured":"Amiri M, Hasanipanah M, Bakhshandeh AH (2020) Predicting ground vibration induced by rock blasting using a novel hybrid of neural network and itemset mining. Neural Comput Appl 32:14681\u201314699. https:\/\/doi.org\/10.1007\/s00521-020-04822-w","journal-title":"Neural Comput Appl"},{"issue":"11","key":"1923_CR4","doi-asserted-by":"publisher","first-page":"1845","DOI":"10.1007\/s42452-020-03611-3","volume":"2","author":"CK Arthur","year":"2020","unstructured":"Arthur CK, Temeng VA, Ziggah YY (2020a) A Self-adaptive differential evolutionary extreme learning machine (SaDE-ELM): a novel approach to blast-induced ground vibration prediction. SN Appl Sci 2(11):1845. https:\/\/doi.org\/10.1007\/s42452-020-03611-3","journal-title":"SN Appl Sci"},{"issue":"1","key":"1923_CR5","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1007\/s00366-018-0686-3","volume":"36","author":"CK Arthur","year":"2020","unstructured":"Arthur CK, Temeng VA, Ziggah YY (2020b) Novel approach to predicting blast-induced ground vibration using Gaussian process regression. Eng Comput 36(1):29\u201342. https:\/\/doi.org\/10.1007\/s00366-018-0686-3","journal-title":"Eng Comput"},{"issue":"1","key":"1923_CR6","doi-asserted-by":"publisher","first-page":"3999","DOI":"10.1038\/s41598-025-86827-w","volume":"15","author":"M Aruna","year":"2025","unstructured":"Aruna M, Vardhan H, Tripathi AK, Parida S, Raja Sekhar Reddy NV, Sivalingam KM, Li Y, Elumalai PV (2025) Enhancing safety in surface mine blasting operations with IoT based ground vibration monitoring and prediction system integrated with machine learning. Sci Rep 15(1):3999. https:\/\/doi.org\/10.1038\/s41598-025-86827-w","journal-title":"Sci Rep"},{"key":"1923_CR7","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1007\/978-1-4302-5990-9_4","volume-title":"Efficient learning machines","author":"M Awad","year":"2015","unstructured":"Awad M, Khanna R (2015) Support vector regression. In: Awad M, Khanna R (eds) Efficient learning machines, 1st edn. Apress Berkeley, Berkeley, pp 67\u201380","edition":"1"},{"key":"1923_CR8","unstructured":"Davies B, Farmer IW, Attewell PB (1964) Ground vibration from shallow sub-surface blasts. Engineer 217(5644):553\u2013559. https:\/\/api.semanticscholar.org\/CorpusID:106560236"},{"issue":"7","key":"1923_CR9","doi-asserted-by":"publisher","first-page":"1895","DOI":"10.1162\/089976698300017197","volume":"10","author":"TG Dietterich","year":"1998","unstructured":"Dietterich TG (1998) Approximate statistical tests for comparing supervised classification learning algorithms. Neural Comput 10(7):1895\u20131923. https:\/\/doi.org\/10.1162\/089976698300017197","journal-title":"Neural Comput"},{"key":"1923_CR10","doi-asserted-by":"publisher","first-page":"2273","DOI":"10.1007\/s00366-020-00937-9","volume":"37","author":"X Ding","year":"2021","unstructured":"Ding X, Hasanipanah M, Nikafshan Rad H, Zhou W (2021) Predicting the blast-induced vibration velocity using a bagged support vector regression optimized with firefly algorithm. Eng Comput 37:2273\u20132284. https:\/\/doi.org\/10.1007\/s00366-020-00937-9","journal-title":"Eng Comput"},{"key":"1923_CR11","unstructured":"Drucker H, Burges CJC, Kaufman L, Smola A, Vapnik VN (1996) Support vector regression machines. Neural Inf. Process. Syst. 9:155\u2013161. https:\/\/api.semanticscholar.org\/CorpusID:743542"},{"key":"1923_CR12","unstructured":"Duvall WI, Petkof B (1958) Spherical propagation of explosion-generated strain pulses in rock. Bureau of mines"},{"key":"1923_CR13","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1007\/s10064-015-0720-2","volume":"75","author":"E Ebrahimi","year":"2016","unstructured":"Ebrahimi E, Monjezi M, Khalesi MR, Armaghani DJ (2016) Prediction and optimization of back-break and rock fragmentation using an artificial neural network and a bee colony algorithm. Bull Eng Geol Environ 75:27\u201336. https:\/\/doi.org\/10.1007\/s10064-015-0720-2","journal-title":"Bull Eng Geol Environ"},{"key":"1923_CR14","doi-asserted-by":"publisher","unstructured":"Elshaarawy MK, Hamed AK (2024) Stacked ensemble model for optimized prediction of triangular side orifice discharge coefficient. Eng Optimiz 1\u201331. https:\/\/doi.org\/10.1080\/0305215X.2024.2397431","DOI":"10.1080\/0305215X.2024.2397431"},{"issue":"2","key":"1923_CR15","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1007\/s12145-025-01755-7","volume":"18","author":"MK Elshaarawy","year":"2025","unstructured":"Elshaarawy MK, Armanuos AM (2025) Predicting seawater intrusion wedge length in coastal aquifers using hybrid gradient boosting techniques. Earth Sci Inform 18(2):243. https:\/\/doi.org\/10.1007\/s12145-025-01755-7","journal-title":"Earth Sci Inform"},{"key":"1923_CR16","unstructured":"Ghosh A, Daemen JJK (1983) A simple new blast vibration predictor (based on wave propagation laws). In: ARMA US symposium on rock mechanics. p. ARMA-83\u20130151"},{"key":"1923_CR17","doi-asserted-by":"publisher","first-page":"107644","DOI":"10.1016\/j.compstruc.2025.107644","volume":"308","author":"AK Hamed","year":"2025","unstructured":"Hamed AK, Elshaarawy M, Alsaadawi MM (2025) Stacked-based machine learning to predict the uniaxial compressive strength of concrete materials. Comput Struct 308:107644. https:\/\/doi.org\/10.1016\/j.compstruc.2025.107644","journal-title":"Comput Struct"},{"key":"1923_CR18","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1016\/j.dib.2018.04.103","volume":"19","author":"OS Hammed","year":"2018","unstructured":"Hammed OS, Popoola OI, Adetoyinbo AA, Awoyemi MO, Adagunodo TA, Olubosede O, Bello AK (2018) Peak particle velocity data acquisition for monitoring blast induced earthquakes in quarry sites. Data Brief 19:398\u2013408. https:\/\/doi.org\/10.1016\/j.dib.2018.04.103","journal-title":"Data Brief"},{"key":"1923_CR19","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1016\/j.measurement.2015.07.019","volume":"75","author":"M Hasanipanah","year":"2015","unstructured":"Hasanipanah M, Monjezi M, Shahnazar A, Jahed Armaghani D, Farazmand A (2015) Feasibility of indirect determination of blast induced ground vibration based on support vector machine. Measurement 75:289\u2013297. https:\/\/doi.org\/10.1016\/j.measurement.2015.07.019","journal-title":"Measurement"},{"key":"1923_CR20","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1007\/s00366-016-0475-9","volume":"33","author":"M Hasanipanah","year":"2017","unstructured":"Hasanipanah M, Faradonbeh RS, Amnieh HB, Armaghani DJ, Monjezi M (2017) Forecasting blast-induced ground vibration developing a CART model. Eng Comput 33:307\u2013316. https:\/\/doi.org\/10.1007\/s00366-016-0475-9","journal-title":"Eng Comput"},{"key":"1923_CR21","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1016\/j.future.2019.02.028","volume":"97","author":"AA Heidari","year":"2019","unstructured":"Heidari AA, Mirjalili S, Faris H, Aljarah I, Mafarja M, Chen H (2019) Harris hawks optimization: algorithm and applications. Futur Gener Comput Syst 97:849\u2013872. https:\/\/doi.org\/10.1016\/j.future.2019.02.028","journal-title":"Futur Gener Comput Syst"},{"key":"1923_CR22","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1016\/j.soildyn.2019.01.011","volume":"119","author":"SA Hosseini","year":"2019","unstructured":"Hosseini SA, Tavana A, Abdolahi SM, Darvishmaslak S (2019) Prediction of blast-induced ground vibrations in quarry sites: a comparison of GP, RSM and MARS. Soil Dyn Earthq Eng 119:118\u2013129. https:\/\/doi.org\/10.1016\/j.soildyn.2019.01.011","journal-title":"Soil Dyn Earthq Eng"},{"key":"1923_CR23","doi-asserted-by":"publisher","first-page":"3221","DOI":"10.1007\/s00366-020-00997-x","volume":"37","author":"D Jahed Armaghani","year":"2021","unstructured":"Jahed Armaghani D, Kumar D, Samui P, Hasanipanah M, Roy B (2021) A novel approach for forecasting of ground vibrations resulting from blasting: modified particle swarm optimization coupled extreme learning machine. Eng Comput 37:3221\u20133235. https:\/\/doi.org\/10.1007\/s00366-020-00997-x","journal-title":"Eng Comput"},{"key":"1923_CR24","doi-asserted-by":"publisher","first-page":"1942","DOI":"10.1109\/ICNN.1995.488968","volume":"4","author":"J Kennedy","year":"1995","unstructured":"Kennedy J, Eberhart R (1995) Particle swarm optimization. Proc. ICNN\u201995 - Int. Conf Neural Networks 4:1942\u20131948. https:\/\/doi.org\/10.1109\/ICNN.1995.488968","journal-title":"Conf Neural Networks"},{"key":"1923_CR25","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1007\/s00366-009-0157-y","volume":"27","author":"M Khandelwal","year":"2011","unstructured":"Khandelwal M, Lalit Kumar D, Yellishetty M (2011) Application of soft computing to predict blast-induced ground vibration. Eng Comput 27:117\u2013125. https:\/\/doi.org\/10.1007\/s00366-009-0157-y","journal-title":"Eng Comput"},{"key":"1923_CR26","volume-title":"The modern technique of rock blasting","author":"U Langefors","year":"1979","unstructured":"Langefors U, Kihlstr\u00f6m B (1979) The modern technique of rock blasting. Wiley, New York"},{"key":"1923_CR27","doi-asserted-by":"publisher","first-page":"1380","DOI":"10.1016\/j.jrmge.2021.07.013","volume":"13","author":"E Li","year":"2021","unstructured":"Li E, Yang F, Ren M, Zhang X, Zhou J, Khandelwal M (2021) Prediction of blasting mean fragment size using support vector regression combined with five optimization algorithms. J Rock Mech Geotech Eng 13:1380\u20131397. https:\/\/doi.org\/10.1016\/j.jrmge.2021.07.013","journal-title":"J Rock Mech Geotech Eng"},{"issue":"1","key":"1923_CR28","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1007\/s11771-022-5208-1","volume":"30","author":"Z Liu","year":"2023","unstructured":"Liu Z, Li D (2023) Intelligent hybrid model to classify failure modes of overstressed rock masses in deep engineering. J Cent South Univ 30(1):156\u2013174. https:\/\/doi.org\/10.1007\/s11771-022-5208-1","journal-title":"J Cent South Univ"},{"key":"1923_CR29","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","volume":"69","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili S, Mirjalili SM, Lewis A (2014) Grey Wolf Optimizer Adv Eng Softw 69:46\u201361. https:\/\/doi.org\/10.1016\/j.advengsoft.2013.12.007","journal-title":"Grey Wolf Optimizer Adv Eng Softw"},{"key":"1923_CR30","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.tust.2010.05.002","volume":"26","author":"M Monjezi","year":"2011","unstructured":"Monjezi M, Ghafurikalajahi M, Bahrami A (2011) Prediction of blast-induced ground vibration using artificial neural networks. Tunn Undergr Sp Technol 26:46\u201350. https:\/\/doi.org\/10.1016\/j.tust.2010.05.002","journal-title":"Tunn Undergr Sp Technol"},{"key":"1923_CR31","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1016\/j.ijrmms.2018.01.038","volume":"103","author":"S Murmu","year":"2018","unstructured":"Murmu S, Maheshwari P, Verma HK (2018) Rock mechanics and mining sciences empirical and probabilistic analysis of blast-induced ground vibrations. Int J Rock Mech Min Sci 103:267\u2013274. https:\/\/doi.org\/10.1016\/j.ijrmms.2018.01.038","journal-title":"Int J Rock Mech Min Sci"},{"key":"1923_CR32","doi-asserted-by":"crossref","unstructured":"Naruei I, Keynia F, Molahosseini AS (2021) Hunter\u2013prey optimization: algorithm and applications. Soft Comput 26:1279\u20131314. https:\/\/api.semanticscholar.org\/CorpusID:244817982","DOI":"10.1007\/s00500-021-06401-0"},{"key":"1923_CR33","doi-asserted-by":"publisher","first-page":"376","DOI":"10.1016\/j.asoc.2019.01.042","volume":"77","author":"H Nguyen","year":"2019","unstructured":"Nguyen H, Bui XN, Tran QH, Mai NL (2019) A new soft computing model for estimating and controlling blast-produced ground vibration based on hierarchical K-means clustering and cubist algorithms. Appl Soft Comput 77:376\u2013386. https:\/\/doi.org\/10.1016\/j.asoc.2019.01.042","journal-title":"Appl Soft Comput"},{"key":"1923_CR34","doi-asserted-by":"publisher","first-page":"691","DOI":"10.1007\/s11053-019-09470-z","volume":"29","author":"H Nguyen","year":"2020","unstructured":"Nguyen H, Drebenstedt C, Bui XN, Bui DT (2020) Prediction of blast-induced ground vibration in an open-pit mine by a novel hybrid model based on clustering and artificial neural network. Nat Resour Res 29:691\u2013709. https:\/\/doi.org\/10.1007\/s11053-019-09470-z","journal-title":"Nat Resour Res"},{"key":"1923_CR35","doi-asserted-by":"publisher","first-page":"4695","DOI":"10.1007\/s11053-021-09896-4","volume":"30","author":"H Nguyen","year":"2021","unstructured":"Nguyen H, Bui XN, Tran QH, Nguyen DA, Hoa LTT, Le QT (2021) Predicting blast-induced ground vibration in open-pit mines using different nature-inspired optimization algorithms and deep neural network. Nat Resour Res 30:4695\u20134717. https:\/\/doi.org\/10.1007\/s11053-021-09896-4","journal-title":"Nat Resour Res"},{"key":"1923_CR36","doi-asserted-by":"publisher","first-page":"109032","DOI":"10.1016\/j.ress.2022.109032","volume":"231","author":"H Nguyen","year":"2023","unstructured":"Nguyen H, Bui XN, Topal E (2023) Reliability and availability artificial intelligence models for predicting blast-induced ground vibration intensity in open-pit mines to ensure the safety of the surroundings. Reliab Eng Syst Saf 231:109032. https:\/\/doi.org\/10.1016\/j.ress.2022.109032","journal-title":"Reliab Eng Syst Saf"},{"key":"1923_CR37","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1016\/0167-9031(91)91642-U","volume":"12","author":"P Pal Roy","year":"1991","unstructured":"Pal Roy P (1991) Vibration control in an opencast mine based on improved blast vibration predictors. Min Sci Technol 12:157\u2013165. https:\/\/doi.org\/10.1016\/0167-9031(91)91642-U","journal-title":"Min Sci Technol"},{"key":"1923_CR38","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1016\/j.undsp.2020.03.002","volume":"6","author":"G Paneiro","year":"2021","unstructured":"Paneiro G, Rafael M (2021) Artificial neural network with a cross-validation approach to blast-induced ground vibration propagation modeling. Undergr Sp 6:281\u2013289. https:\/\/doi.org\/10.1016\/j.undsp.2020.03.002","journal-title":"Undergr Sp"},{"key":"1923_CR39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-50920-4","volume-title":"Nature-inspired computing and optimization","author":"S Patnaik","year":"2017","unstructured":"Patnaik S, Yang X-S, Nakamatsu K (2017) Nature-inspired computing and optimization. Springer"},{"key":"1923_CR40","unstructured":"Raia R, Singh TN (2004) A new predictor for ground vibration prediction and its comparison with other predictors. Indian J Eng Mater Sci 11:178\u2013184. https:\/\/api.semanticscholar.org\/CorpusID:114547528"},{"key":"1923_CR41","volume-title":"Fuzzy logic with engineering","author":"TJ Ross","year":"2010","unstructured":"Ross TJ (2010) Fuzzy logic with engineering. Wiley"},{"key":"1923_CR42","doi-asserted-by":"publisher","first-page":"9679","DOI":"10.1007\/s12517-015-1923-3","volume":"8","author":"H Samareh","year":"2015","unstructured":"Samareh H, Khoshrou SH, Shahriar K, Saberi MM (2015) Seismic data classification using cluster analysis for predicting ground vibration caused by blast. Arab J Geosci 8:9679\u20139692. https:\/\/doi.org\/10.1007\/s12517-015-1923-3","journal-title":"Arab J Geosci"},{"key":"1923_CR43","doi-asserted-by":"publisher","first-page":"547","DOI":"10.1007\/s00603-008-0014-0","volume":"42","author":"L Sambuelli","year":"2009","unstructured":"Sambuelli L (2009) Theoretical derivation of a peak particle velocity-distance law for the prediction of vibrations from blasting. Rock Mech Rock Eng 42:547\u2013556. https:\/\/doi.org\/10.1007\/s00603-008-0014-0","journal-title":"Rock Mech Rock Eng"},{"key":"1923_CR44","doi-asserted-by":"publisher","first-page":"723","DOI":"10.1007\/s11053-019-09503-7","volume":"29","author":"Y Shang","year":"2020","unstructured":"Shang Y, Nguyen H, Bui XN, Tran QH, Moayedi H (2020) A novel artificial intelligence approach to predict blast-induced ground vibration in open-pit mines based on the firefly algorithm and artificial neural network. Nat Resour Res 29:723\u2013737. https:\/\/doi.org\/10.1007\/s11053-019-09503-7","journal-title":"Nat Resour Res"},{"issue":"D7","key":"1923_CR45","doi-asserted-by":"publisher","first-page":"7183","DOI":"10.1029\/2000JD900719","volume":"106","author":"KE Taylor","year":"2001","unstructured":"Taylor KE (2001) Summarizing multiple aspects of model\u2019s performance in a single diagram. J Geophys Res 106(D7):7183\u20137192. https:\/\/doi.org\/10.1029\/2000JD900719","journal-title":"J Geophys Res"},{"key":"1923_CR46","doi-asserted-by":"publisher","first-page":"102732","DOI":"10.1016\/j.flowmeasinst.2024.102732","volume":"100","author":"W Tian","year":"2024","unstructured":"Tian W, Isleem HF, Hamed AK, Elshaarawy MK (2024) Enhancing discharge prediction over Type-A piano key weirs: An innovative machine learning approach. Flow Meas Instrum 100:102732. https:\/\/doi.org\/10.1016\/j.flowmeasinst.2024.102732","journal-title":"Flow Meas Instrum"},{"key":"1923_CR47","unstructured":"Vapnik V (2013) The nature of statistical learning theory. Springer science & business media"},{"key":"1923_CR48","doi-asserted-by":"publisher","first-page":"1241","DOI":"10.1007\/s00366-020-01082-z","volume":"38","author":"H Wei","year":"2022","unstructured":"Wei H, Chen J, Zhu J, Yang X, Chu H (2022) A novel algorithm of Nested-ELM for predicting blasting vibration. Eng Comput 38:1241\u20131256. https:\/\/doi.org\/10.1007\/s00366-020-01082-z","journal-title":"Eng Comput"},{"key":"1923_CR49","unstructured":"Wiss JF, Linehan PW (1978) Control of vibration and blast noise from surface coal mining. Bureau of Mines. https:\/\/api.semanticscholar.org\/CorpusID:109251130"},{"key":"1923_CR50","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1080\/21642583.2019.1708830","volume":"8","author":"J Xue","year":"2020","unstructured":"Xue J, Shen B (2020) A novel swarm intelligence optimization approach: sparrow search algorithm. Syst Sci Control Eng 8:22\u201334. https:\/\/doi.org\/10.1080\/21642583.2019.1708830","journal-title":"Syst Sci Control Eng"},{"key":"1923_CR51","doi-asserted-by":"publisher","first-page":"739","DOI":"10.1007\/s11053-019-09515-3","volume":"29","author":"H Yang","year":"2020","unstructured":"Yang H, Hasanipanah M, Tahir MM, Bui DT (2020) Intelligent prediction of blasting-induced ground vibration using ANFIS optimized by GA and PSO. Nat Resour Res 29:739\u2013750. https:\/\/doi.org\/10.1007\/s11053-019-09515-3","journal-title":"Nat Resour Res"},{"issue":"4","key":"1923_CR52","doi-asserted-by":"publisher","first-page":"1403","DOI":"10.3390\/app10041403","volume":"10","author":"Z Yu","year":"2020","unstructured":"Yu Z, Shi X, Zhou J, Chen X, Qiu X (2020) Effective assessment of blast-induced ground vibration using an optimized random forest model based on a harris hawks optimization algorithm. Appl Sci 10(4):1403. https:\/\/doi.org\/10.3390\/app10041403","journal-title":"Appl Sci"},{"key":"1923_CR53","doi-asserted-by":"publisher","first-page":"2647","DOI":"10.1007\/s11053-021-09826-4","volume":"30","author":"C Yu","year":"2021","unstructured":"Yu C, Koopialipoor M, Murlidhar BR, Mohammed AS, Jahed Armaghani D, Mohamad ET, Wang Z (2021) Optimal ELM\u2013Harris Hawks optimization and ELM\u2013Grasshopper optimization models to forecast peak particle velocity resulting from mine blasting. Nat Resour Res 30:2647\u20132662. https:\/\/doi.org\/10.1007\/s11053-021-09826-4","journal-title":"Nat Resour Res"},{"key":"1923_CR54","volume-title":"Rock fracture and blasting: theory and applications","author":"Z-X Zhang","year":"2016","unstructured":"Zhang Z-X (2016) Rock fracture and blasting: theory and applications. Butterworth-Heinemann"},{"key":"1923_CR55","doi-asserted-by":"publisher","DOI":"10.1002\/suco.202400886","author":"J Zhang","year":"2025","unstructured":"Zhang J, Almoghayer WJK, Isleem HF, Negi BS, Mahmoud HA, Elshaarawy MK (2025) Machine learning for the prediction of the axial load-carrying capacity of FRP reinforced hollow concrete column. Struct Concrete. https:\/\/doi.org\/10.1002\/suco.202400886","journal-title":"Struct Concrete"},{"key":"1923_CR56","doi-asserted-by":"publisher","first-page":"106390","DOI":"10.1016\/j.soildyn.2020.106390","volume":"139","author":"J Zhou","year":"2020","unstructured":"Zhou J, Asteris PG, Armaghani DJ, Pham BT (2020) Prediction of ground vibration induced by blasting operations through the use of the bayesian network and random forest models. Soil Dyn Earthq Eng 139:106390. https:\/\/doi.org\/10.1016\/j.soildyn.2020.106390","journal-title":"Soil Dyn Earthq Eng"},{"key":"1923_CR57","doi-asserted-by":"publisher","first-page":"107434","DOI":"10.1016\/j.asoc.2021.107434","volume":"108","author":"W Zhu","year":"2021","unstructured":"Zhu W, Nikafshan Rad H, Hasanipanah M (2021) A chaos recurrent ANFIS optimized by PSO to predict ground vibration generated in rock blasting. Appl Soft Comput 108:107434. https:\/\/doi.org\/10.1016\/j.asoc.2021.107434","journal-title":"Appl Soft Comput"}],"container-title":["Earth Science Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12145-025-01923-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12145-025-01923-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12145-025-01923-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,6]],"date-time":"2025-09-06T16:31:57Z","timestamp":1757176317000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12145-025-01923-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,31]]},"references-count":57,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,6]]}},"alternative-id":["1923"],"URL":"https:\/\/doi.org\/10.1007\/s12145-025-01923-9","relation":{},"ISSN":["1865-0473","1865-0481"],"issn-type":[{"type":"print","value":"1865-0473"},{"type":"electronic","value":"1865-0481"}],"subject":[],"published":{"date-parts":[[2025,5,31]]},"assertion":[{"value":"16 December 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 May 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 May 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"424"}}