{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T09:41:30Z","timestamp":1767865290863,"version":"3.49.0"},"reference-count":71,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2019,7,25]],"date-time":"2019-07-25T00:00:00Z","timestamp":1564012800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,7,25]],"date-time":"2019-07-25T00:00:00Z","timestamp":1564012800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2020,6]]},"DOI":"10.1007\/s00521-019-04353-z","type":"journal-article","created":{"date-parts":[[2019,7,25]],"date-time":"2019-07-25T17:02:37Z","timestamp":1564074157000},"page":"8545-8559","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":52,"title":["Application of self-organizing map and fuzzy c-mean techniques for rockburst clustering in deep underground projects"],"prefix":"10.1007","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1518-3597","authenticated-orcid":false,"given":"Roohollah","family":"Shirani Faradonbeh","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sina","family":"Shaffiee Haghshenas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abbas","family":"Taheri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Reza","family":"Mikaeil","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,7,25]]},"reference":[{"key":"4353_CR1","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1016\/S1365-1609(99)00072-6","volume":"37","author":"J Sun","year":"2000","unstructured":"Sun J, Wang S (2000) Rock mechanics and rock engineering in China: developments and current state-of-the-art. Int J Rock Mech Min Sci 37:447\u2013465. https:\/\/doi.org\/10.1016\/S1365-1609(99)00072-6","journal-title":"Int J Rock Mech Min Sci"},{"key":"4353_CR2","doi-asserted-by":"publisher","first-page":"629","DOI":"10.1016\/j.ssci.2011.08.065","volume":"50","author":"Z Jian","year":"2012","unstructured":"Jian Z, Xibing L, Xiuzhi S (2012) Long-term prediction model of rockburst in underground openings using heuristic algorithms and support vector machines. Saf Sci 50:629\u2013644. https:\/\/doi.org\/10.1016\/j.ssci.2011.08.065","journal-title":"Saf Sci"},{"issue":"6","key":"4353_CR3","doi-asserted-by":"publisher","first-page":"1657","DOI":"10.1007\/s00603-018-1415-3","volume":"51","author":"S Akdag","year":"2018","unstructured":"Akdag S, Karakus M, Taheri A et al (2018) Effects of thermal damage on strain burst mechanism for brittle rocks under true-triaxial loading conditions. Rock Mech Rock Eng 51(6):1657\u20131682. https:\/\/doi.org\/10.1007\/s00603-018-1415-3","journal-title":"Rock Mech Rock Eng"},{"key":"4353_CR4","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1016\/j.tust.2017.05.011","volume":"69","author":"L Weng","year":"2017","unstructured":"Weng L, Huang L, Taheri A, Li X (2017) Rockburst characteristics and numerical simulation based on a strain energy density index: a case study of a roadway in Linglong gold mine, China. Tunn Undergr Space Technol 69:223\u2013232. https:\/\/doi.org\/10.1016\/j.tust.2017.05.011","journal-title":"Tunn Undergr Space Technol"},{"key":"4353_CR5","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1016\/j.tust.2015.10.002","volume":"51","author":"XT Feng","year":"2016","unstructured":"Feng XT, Yu Y, Feng GL et al (2016) Fractal behaviour of the microseismic energy associated with immediate rockbursts in deep, hard rock tunnels. Tunn Undergr Sp Technol 51:98\u2013107. https:\/\/doi.org\/10.1016\/j.tust.2015.10.002","journal-title":"Tunn Undergr Sp Technol"},{"key":"4353_CR6","doi-asserted-by":"publisher","first-page":"1149","DOI":"10.1016\/j.ijrmms.2007.06.002","volume":"44","author":"T Li","year":"2007","unstructured":"Li T, Cai MF, Cai M (2007) A review of mining-induced seismicity in China. Int J Rock Mech Min Sci 44:1149\u20131171. https:\/\/doi.org\/10.1016\/j.ijrmms.2007.06.002","journal-title":"Int J Rock Mech Min Sci"},{"key":"4353_CR7","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/J.IJRMMS.2017.01.005","volume":"93","author":"J He","year":"2017","unstructured":"He J, Dou L, Gong S et al (2017) Rock burst assessment and prediction by dynamic and static stress analysis based on micro-seismic monitoring. Int J Rock Mech Min Sci 93:46\u201353. https:\/\/doi.org\/10.1016\/J.IJRMMS.2017.01.005","journal-title":"Int J Rock Mech Min Sci"},{"key":"4353_CR8","volume-title":"Rockbursts: case studies from North American hard-rock mines","author":"W Blake","year":"2003","unstructured":"Blake W, Hedley DG (2003) Rockbursts: case studies from North American hard-rock mines. Markham, SME"},{"key":"4353_CR9","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1016\/j.enggeo.2015.01.011","volume":"188","author":"P Yan","year":"2015","unstructured":"Yan P, Zhao Z, Lu W et al (2015) Mitigation of rock burst events by blasting techniques during deep-tunnel excavation. Eng Geol 188:126\u2013136. https:\/\/doi.org\/10.1016\/j.enggeo.2015.01.011","journal-title":"Eng Geol"},{"key":"4353_CR10","doi-asserted-by":"publisher","first-page":"632","DOI":"10.1016\/j.tust.2018.08.029","volume":"81","author":"J Zhou","year":"2018","unstructured":"Zhou J, Li X, Mitri HS (2018) Evaluation method of rockburst: state-of-the-art literature review. Tunn Undergr Sp Technol 81:632\u2013659. https:\/\/doi.org\/10.1016\/j.tust.2018.08.029","journal-title":"Tunn Undergr Sp Technol"},{"key":"4353_CR11","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1016\/j.enggeo.2014.12.008","volume":"185","author":"M He","year":"2015","unstructured":"He M, e Sousa LR, Miranda T, Zhu G (2015) Rockburst laboratory tests database - Application of data mining techniques. Eng Geol 185:116\u2013130. https:\/\/doi.org\/10.1016\/j.enggeo.2014.12.008","journal-title":"Eng Geol"},{"key":"4353_CR12","doi-asserted-by":"crossref","unstructured":"Castro L, Bewick R, Carter T (2012) An overview of numerical modelling applied to deep mining. In: Innovative numerical modelling in geomechanics. CRC Press, pp 393\u2013414","DOI":"10.1201\/b12130-22"},{"key":"4353_CR13","doi-asserted-by":"publisher","first-page":"193","DOI":"10.3724\/SP.J.1235.2010.00193","volume":"2","author":"C Tang","year":"2010","unstructured":"Tang C, Wang J, Zhang J (2010) Preliminary engineering application of microseismic monitoring technique to rockburst prediction in tunneling of Jinping II project. J Rock Mech Geotech Eng 2:193\u2013208. https:\/\/doi.org\/10.3724\/SP.J.1235.2010.00193","journal-title":"J Rock Mech Geotech Eng"},{"issue":"1","key":"4353_CR14","first-page":"2720","volume":"29","author":"XZ Shi","year":"2010","unstructured":"Shi XZ, Zhou J, Dong L et al (2010) Application of unascertained measurement model to prediction of classification of rockburst intensity. Chinese J Rock Mech Eng 29(1):2720\u20132727 (in Chinese)","journal-title":"Chinese J Rock Mech Eng"},{"key":"4353_CR15","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1016\/j.jrmge.2015.11.002","volume":"8","author":"M Cai","year":"2016","unstructured":"Cai M (2016) Prediction and prevention of rockburst in metal mines\u2014a case study of Sanshandao gold mine. J Rock Mech Geotech Eng 8:204\u2013211. https:\/\/doi.org\/10.1016\/j.jrmge.2015.11.002","journal-title":"J Rock Mech Geotech Eng"},{"key":"4353_CR16","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1016\/0031-9201(72)90005-2","volume":"6","author":"IA Turchaninov","year":"1972","unstructured":"Turchaninov IA, Markov GA, Gzovsky MV et al (1972) State of stress in the upper part of the Earth\u2019s crust based on direct measurements in mines and on tectonophysical and seismological studies. Phys Earth Planet Inter 6:229\u2013234. https:\/\/doi.org\/10.1016\/0031-9201(72)90005-2","journal-title":"Phys Earth Planet Inter"},{"key":"4353_CR17","unstructured":"Russenes B (1974) Analysis of rock spalling for tunnels in steep valley sides. Master Thesis of Science, Norwegian Institute of Technology"},{"key":"4353_CR18","volume-title":"Underground excavations in rock","author":"E Hoek","year":"1980","unstructured":"Hoek E, Brown ET (1980) Underground excavations in rock. Institution of Mining and Metallurgy, London"},{"key":"4353_CR19","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1007\/BF01239496","volume":"6","author":"N Barton","year":"1974","unstructured":"Barton N, Lien R, Lunde J (1974) Engineering classification of rock masses for the design of tunnel support. Rock Mech Felsmechanik M\u00e9canique des Roches 6:189\u2013236. https:\/\/doi.org\/10.1007\/BF01239496","journal-title":"Rock Mech Felsmechanik M\u00e9canique des Roches"},{"issue":"5","key":"4353_CR20","first-page":"493","volume":"17","author":"YH Wang","year":"1998","unstructured":"Wang YH, Li WD, Lee PKK, Tham LG (1998) method of fuzzy comprehensive evaluations for rockburst prediction. Chin J Rock Mech Eng 17(5):493\u2013501 (in Chinese)","journal-title":"Chin J Rock Mech Eng"},{"key":"4353_CR21","unstructured":"Aubertin M, Gill DE, Simon R, others (1994) On the use of the brittleness index modified (BIM) to estimate the post-peak behavior of rocks. In: 1st North American rock mechanics symposium"},{"issue":"6","key":"4353_CR22","first-page":"513","volume":"21","author":"C Li","year":"1996","unstructured":"Li C, Cai M, Qiao L, Wang S (1996) Rock complete stress-strain curve and its relationship to rockburst. J Univ Sci Technol Beijing 21(6):513\u2013515 (in Chinese)","journal-title":"J Univ Sci Technol Beijing"},{"key":"4353_CR23","unstructured":"Mo C, Tan H, Su G, Jiang J (2014) A new rockburst proneness index based on energy principle. International Conference on Civil Engineering, Energy and Environment"},{"key":"4353_CR24","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1016\/0148-9062(94)92316-7","volume":"31","author":"PC Jha","year":"1994","unstructured":"Jha PC, Chouhan RKS (1994) Long range rockburst prediction: a seismological approach. Int J Rock Mech Min Sci 31:71\u201377. https:\/\/doi.org\/10.1016\/0148-9062(94)92316-7","journal-title":"Int J Rock Mech Min Sci"},{"key":"4353_CR25","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1007\/BF01045719","volume":"30","author":"V Frid","year":"1997","unstructured":"Frid V (1997) Rockburst hazard forecast by electromagnetic radiation excited by rock fracture. Rock Mech Rock Eng 30:229\u2013236. https:\/\/doi.org\/10.1007\/BF01045719","journal-title":"Rock Mech Rock Eng"},{"key":"4353_CR26","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.ijrmms.2014.01.007","volume":"67","author":"M He","year":"2014","unstructured":"He M, Gong W, Wang J et al (2014) Development of a novel energy-absorbing bolt with extraordinarily large elongation and constant resistance. Int J Rock Mech Min Sci 67:29\u201342. https:\/\/doi.org\/10.1016\/j.ijrmms.2014.01.007","journal-title":"Int J Rock Mech Min Sci"},{"key":"4353_CR27","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1016\/S1674-5264(09)60109-5","volume":"19","author":"LM Dou","year":"2009","unstructured":"Dou LM, Lu CP, Mu ZL, Gao MS (2009) Prevention and forecasting of rock burst hazards in coal mines. Min Sci Technol 19:585\u2013591. https:\/\/doi.org\/10.1016\/S1674-5264(09)60109-5","journal-title":"Min Sci Technol"},{"key":"4353_CR28","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1016\/j.enggeo.2016.11.014","volume":"216","author":"G Zhao","year":"2017","unstructured":"Zhao G, Wang D, Gao B, Wang S (2017) Modifying rock burst criteria based on observations in a division tunnel. Eng Geol 216:153\u2013160. https:\/\/doi.org\/10.1016\/j.enggeo.2016.11.014","journal-title":"Eng Geol"},{"key":"4353_CR29","doi-asserted-by":"publisher","first-page":"549","DOI":"10.1007\/s11069-013-0635-9","volume":"68","author":"Z Liu","year":"2013","unstructured":"Liu Z, Shao J, Xu W, Meng Y (2013) Prediction of rock burst classification using the technique of cloud models with attribution weight. Nat Hazards 68:549\u2013568. https:\/\/doi.org\/10.1007\/s11069-013-0635-9","journal-title":"Nat Hazards"},{"key":"4353_CR30","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.tust.2016.09.010","volume":"61","author":"N Li","year":"2017","unstructured":"Li N, Feng X, Jimenez R (2017) Predicting rock burst hazard with incomplete data using Bayesian networks. Tunn Undergr Sp Technol 61:61\u201370. https:\/\/doi.org\/10.1016\/j.tust.2016.09.010","journal-title":"Tunn Undergr Sp Technol"},{"issue":"1","key":"4353_CR31","first-page":"7","volume":"4","author":"X Feng","year":"1994","unstructured":"Feng X, Wang L (1994) Rockburst prediction based on neural networks. Trans Nonferrous Met Soc China 4(1):7\u201314","journal-title":"Trans Nonferrous Met Soc China"},{"issue":"2","key":"4353_CR32","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1007\/s12404-010-0207-5","volume":"16","author":"J Zhou","year":"2010","unstructured":"Zhou J, Shi XZ, Dong L et al (2010) Fisher discriminant analysis model and its application for prediction of classification of rockburst in deepburied long tunnel. J Coal Sci Eng 16(2):144\u2013149","journal-title":"J Coal Sci Eng"},{"key":"4353_CR33","first-page":"41","volume":"33","author":"Q Zhang","year":"2011","unstructured":"Zhang Q, Wang W, Liu T (2011) Prediction of rock bursts based on particle swarm optimization-BP neural network. J China Three Gorges Univ 33:41\u201345","journal-title":"J China Three Gorges Univ"},{"key":"4353_CR34","first-page":"57","volume":"33","author":"B Li","year":"2015","unstructured":"Li B, Liu Y (2015) Determination of classification of rock burst risk based on random forest approach and its application. Sci Technol Rev 33:57\u201362","journal-title":"Sci Technol Rev"},{"key":"4353_CR35","first-page":"16","volume":"34","author":"X-B Xie","year":"2007","unstructured":"Xie X-B, Pan C-L (2007) Rockburst prediction method based on grey whitenization weight function cluster theory. Hunan Daxue Xuebao\/Journal Hunan Univ Nat Sci 34:16\u201320","journal-title":"Hunan Daxue Xuebao\/Journal Hunan Univ Nat Sci"},{"key":"4353_CR36","first-page":"874","volume":"32","author":"W Gao","year":"2010","unstructured":"Gao W (2010) Prediction of rock burst based on ant colony clustering algorithm. Yantu Gongcheng Xuebao\/Chin J Geotech Eng 32:874\u2013880","journal-title":"Yantu Gongcheng Xuebao\/Chin J Geotech Eng"},{"key":"4353_CR37","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1007\/s00603-013-0524-2","volume":"48","author":"BR Chen","year":"2013","unstructured":"Chen BR, Feng XT, Li QP et al (2013) Rock Burst Intensity Classification Based on the Radiated Energy with Damage Intensity at Jinping II Hydropower Station, China. Rock Mech Rock Eng 48:289\u2013303. https:\/\/doi.org\/10.1007\/s00603-013-0524-2","journal-title":"Rock Mech Rock Eng"},{"key":"4353_CR38","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1016\/j.compgeo.2008.02.005","volume":"36","author":"SK Das","year":"2009","unstructured":"Das SK, Basudhar PK (2009) Utilization of self-organizing map and fuzzy clustering for site characterization using piezocone data. Comput Geotech 36:241\u2013248. https:\/\/doi.org\/10.1016\/j.compgeo.2008.02.005","journal-title":"Comput Geotech"},{"key":"4353_CR39","unstructured":"Rad MY, Haghshenas SS, Kanafi PR, Haghshenas SS (2012) Analysis of protection of body slope in the rockfill reservoir dams on the basis of fuzzy logic. In IJCCI, pp 367\u2013373"},{"key":"4353_CR40","doi-asserted-by":"publisher","first-page":"1309","DOI":"10.1007\/s10706-017-0394-6","volume":"36","author":"R Mikaeil","year":"2018","unstructured":"Mikaeil R, Haghshenas SS, Hoseinie SH (2018) Rock penetrability classification using artificial bee colony (ABC) algorithm and self-organizing map. Geotech Geol Eng 36:1309\u20131318. https:\/\/doi.org\/10.1007\/s10706-017-0394-6","journal-title":"Geotech Geol Eng"},{"issue":"2","key":"4353_CR41","doi-asserted-by":"publisher","first-page":"3779","DOI":"10.1007\/s10706-018-0571-2","volume":"36","author":"R Mikaeil","year":"2018","unstructured":"Mikaeil R, Haghshenas SS, Ozcelik Y, Gharehgheshlagh HH (2018) Performance evaluation of adaptive neuro-fuzzy inference system and group method of data handling-type neural network for estimating wear rate of diamond wire saw. Geotech Geol Eng 36(2):3779\u20133791. https:\/\/doi.org\/10.1007\/s10706-018-0571-2","journal-title":"Geotech Geol Eng"},{"key":"4353_CR42","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1016\/j.ijrmms.2016.07.028","volume":"88","author":"RS Faradonbeh","year":"2016","unstructured":"Faradonbeh RS, Armaghani DJ, Monjezi M, Mohamad ET (2016) Genetic programming and gene expression programming for flyrock assessment due to mine blasting. Int J Rock Mech Min Sci 88:254. https:\/\/doi.org\/10.1016\/j.ijrmms.2016.07.028","journal-title":"Int J Rock Mech Min Sci"},{"key":"4353_CR43","doi-asserted-by":"publisher","first-page":"739","DOI":"10.1007\/s12665-016-5524-6","volume":"75","author":"M Khandelwal","year":"2016","unstructured":"Khandelwal M, Armaghani DJ, Faradonbeh RS et al (2016) A new model based on gene expression programming to estimate air flow in a single rock joint. Environ Earth Sci 75:739. https:\/\/doi.org\/10.1007\/s12665-016-5524-6","journal-title":"Environ Earth Sci"},{"key":"4353_CR44","doi-asserted-by":"publisher","first-page":"1115","DOI":"10.1007\/s00521-016-2618-8","volume":"29","author":"DJ Armaghani","year":"2016","unstructured":"Armaghani DJ, Faradonbeh RS, Rezaei H et al (2016) Settlement prediction of the rock-socketed piles through a new technique based on gene expression programming. Neural Comput Appl 29:1115\u20131125. https:\/\/doi.org\/10.1007\/s00521-016-2618-8","journal-title":"Neural Comput Appl"},{"key":"4353_CR45","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1007\/s00366-016-0455-0","volume":"33","author":"M Khandelwal","year":"2017","unstructured":"Khandelwal M, Armaghani DJ, Faradonbeh RS et al (2017) Classification and regression\u00a0tree technique in estimating peak particle velocity caused by blasting. Eng Comput 33:45\u201353. https:\/\/doi.org\/10.1007\/s00366-016-0455-0","journal-title":"Eng Comput"},{"key":"4353_CR46","doi-asserted-by":"publisher","first-page":"1978","DOI":"10.1007\/s12205-017-2039-y","volume":"22","author":"A Salemi","year":"2018","unstructured":"Salemi A, Mikaeil R, Haghshenas SS (2018) Integration of finite difference method and genetic algorithm to seismic analysis of circular shallow tunnels (Case Study: Tabriz Urban Railway Tunnels). KSCE J Civ Eng 22:1978\u20131990. https:\/\/doi.org\/10.1007\/s12205-017-2039-y","journal-title":"KSCE J Civ Eng"},{"key":"4353_CR47","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1016\/j.measurement.2018.03.056","volume":"124","author":"A Aryafar","year":"2018","unstructured":"Aryafar A, Mikaeil R, Haghshenas SS, Haghshenas SS (2018) Application of metaheuristic algorithms to optimal clustering of sawing machine vibration. Meas J Int Meas Confed 124:20\u201331. https:\/\/doi.org\/10.1016\/j.measurement.2018.03.056","journal-title":"Meas J Int Meas Confed"},{"key":"4353_CR48","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1007\/s00521-016-2359-8","volume":"28","author":"ET Mohamad","year":"2016","unstructured":"Mohamad ET, Faradonbeh RS, Armaghani DJ et al (2016) An optimized ANN model based on genetic algorithm for predicting ripping production. Neural Comput Appl 28:393\u2013406. https:\/\/doi.org\/10.1007\/s00521-016-2359-8","journal-title":"Neural Comput Appl"},{"key":"4353_CR49","doi-asserted-by":"publisher","first-page":"3537","DOI":"10.1007\/s00521-016-2263-2","volume":"28","author":"S Mahdevari","year":"2017","unstructured":"Mahdevari S, Shahriar K, Sharifzadeh M, Tannant DD (2017) Stability prediction of gate roadways in longwall mining using artificial neural networks. Neural Comput Appl 28:3537\u20133555. https:\/\/doi.org\/10.1007\/s00521-016-2263-2","journal-title":"Neural Comput Appl"},{"key":"4353_CR50","doi-asserted-by":"publisher","first-page":"1464","DOI":"10.1109\/5.58325","volume":"78","author":"T Kohonen","year":"1990","unstructured":"Kohonen T (1990) The self-organizing map. Proc IEEE 78:1464\u20131480. https:\/\/doi.org\/10.1109\/5.58325","journal-title":"Proc IEEE"},{"key":"4353_CR51","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/J.RESS.2015.02.011","volume":"139","author":"H Yu","year":"2015","unstructured":"Yu H, Khan F, Garaniya V (2015) Risk-based fault detection using self-organizing map. Reliab Eng Syst Saf 139:82\u201396. https:\/\/doi.org\/10.1016\/J.RESS.2015.02.011","journal-title":"Reliab Eng Syst Saf"},{"key":"4353_CR52","doi-asserted-by":"publisher","first-page":"572","DOI":"10.1016\/j.ins.2018.12.007","volume":"496","author":"A Malondkar","year":"2018","unstructured":"Malondkar A, Corizzo R, Kiringa I et al (2018) Spark-GHSOM: growing hierarchical self-organizing map for large scale mixed attribute datasets. Inf Sci 496:572\u2013591. https:\/\/doi.org\/10.1016\/j.ins.2018.12.007","journal-title":"Inf Sci"},{"key":"4353_CR53","volume-title":"Neural network design","author":"MT Hagan","year":"1996","unstructured":"Hagan MT, Demuth HB, Beale MH et al (1996) Neural network design. Pws Pub, Boston"},{"key":"4353_CR54","volume-title":"Neural network design","author":"HB Demuth","year":"2014","unstructured":"Demuth HB, Beale MH, De Jess O, Hagan MT (2014) Neural network design. Martin Hagan, Stillwater"},{"key":"4353_CR55","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1142\/9789814261302_0021","volume-title":"Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers","author":"LA Zadeh","year":"1996","unstructured":"Zadeh LA (1996) Fuzzy sets. In: Zadeh LA (ed) Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers. World Scientific, Singapore, pp 394\u2013432"},{"key":"4353_CR56","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/978-1-4757-0450-1","volume-title":"Pattern recognition with fuzzy objective function algorithms","author":"JC Bezdek","year":"1981","unstructured":"Bezdek JC (1981) Models for pattern recognition. In: Bezdek JC (ed) Pattern recognition with fuzzy objective function algorithms. Springer, Boston, pp 1\u201313"},{"key":"4353_CR57","first-page":"197","volume-title":"Self-organizing maps and fuzzy c-means algorithms on gait analysis based on inertial sensors data","author":"R Caldas","year":"2017","unstructured":"Caldas R, Hu Y, de Lima Neto FB, Markert B (2017) Self-organizing maps and fuzzy c-means algorithms on gait analysis based on inertial sensors data. Springer, Cham, pp 197\u2013205"},{"key":"4353_CR58","doi-asserted-by":"publisher","first-page":"472","DOI":"10.1016\/S1003-6326(13)62487-5","volume":"23","author":"L Dong","year":"2013","unstructured":"Dong L, Li X, Peng K (2013) Prediction of rockburst classification using Random Forest. Trans Nonferrous Met Soc China 23:472\u2013477. https:\/\/doi.org\/10.1016\/S1003-6326(13)62487-5","journal-title":"Trans Nonferrous Met Soc China"},{"key":"4353_CR59","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1016\/j.ijrmms.2013.02.010","volume":"61","author":"AC Adoko","year":"2013","unstructured":"Adoko AC, Gokceoglu C, Wu L, Zuo QJ (2013) Knowledge-based and data-driven fuzzy modeling for rockburst prediction. Int J Rock Mech Min Sci 61:86\u201395. https:\/\/doi.org\/10.1016\/j.ijrmms.2013.02.010","journal-title":"Int J Rock Mech Min Sci"},{"key":"4353_CR60","unstructured":"Palmstrom A (1995) Characterizing the strength of rock masses for use in design of underground structures. In: In: International conference in design and construction of underground structures. p 10"},{"key":"4353_CR61","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1016\/j.enggeo.2016.11.014","volume":"216","author":"G Zhao","year":"2017","unstructured":"Zhao G, Wang D, Gao B, Wang S (2017) Modifying rock burst criteria based on observations in a division tunnel. Eng Geol 216:153\u2013160. https:\/\/doi.org\/10.1016\/j.enggeo.2016.11.014","journal-title":"Eng Geol"},{"key":"4353_CR62","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1016\/0148-9062(81)91194-3","volume":"18","author":"A Kidybi\u0144ski","year":"1981","unstructured":"Kidybi\u0144ski A (1981) Bursting liability indices of coal. Int J Rock Mech Min Sci 18:295\u2013304. https:\/\/doi.org\/10.1016\/0148-9062(81)91194-3","journal-title":"Int J Rock Mech Min Sci"},{"key":"4353_CR63","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s00366-018-0624-4","volume":"35","author":"R Shirani Faradonbeh","year":"2018","unstructured":"Shirani Faradonbeh R, Taheri A (2018) Long-term prediction of rockburst hazard in deep underground openings using three robust data mining techniques. Eng Comput 35:1\u201317. https:\/\/doi.org\/10.1007\/s00366-018-0624-4","journal-title":"Eng Comput"},{"key":"4353_CR64","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1007\/s00521-016-2557-4","volume":"29","author":"R Mikaeil","year":"2018","unstructured":"Mikaeil R, Haghshenas SS, Haghshenas SS, Ataei M (2018) Performance prediction of circular saw machine using imperialist competitive algorithm and fuzzy clustering technique. Neural Comput Appl 29:283\u2013292. https:\/\/doi.org\/10.1007\/s00521-016-2557-4","journal-title":"Neural Comput Appl"},{"key":"4353_CR65","doi-asserted-by":"publisher","first-page":"1941","DOI":"10.1007\/s00477-016-1334-3","volume":"31","author":"F Rezaei","year":"2017","unstructured":"Rezaei F, Ahmadzadeh MR, Safavi HR (2017) SOM-DRASTIC: using self-organizing map for evaluating groundwater potential to pollution. Stoch Environ Res Risk Assess 31:1941\u20131956. https:\/\/doi.org\/10.1007\/s00477-016-1334-3","journal-title":"Stoch Environ Res Risk Assess"},{"key":"4353_CR66","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1504\/IJMR.2018.093252","volume":"30","author":"ZY Chen","year":"2017","unstructured":"Chen ZY, Kuo RJ (2017) Combining SOM and evolutionary computation algorithms for RBF neural network training. J Intell Manuf 30:1\u201318","journal-title":"J Intell Manuf"},{"key":"4353_CR67","unstructured":"Rad MY, Haghshenas SS, Haghshenas SS (2014) Mechanostratigraphy of cretaceous rocks by fuzzy logic in East Arak, Iran. In: The 4th international workshop on computer science and engineering-summer, WCSE"},{"key":"4353_CR68","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1016\/j.geoderma.2007.11.004","volume":"143","author":"C Grinand","year":"2008","unstructured":"Grinand C, Arrouays D, Laroche B, Martin MP (2008) Extrapolating regional soil landscapes from an existing soil map: sampling intensity, validation procedures, and integration of spatial context. Geoderma 143:180\u2013190. https:\/\/doi.org\/10.1016\/j.geoderma.2007.11.004","journal-title":"Geoderma"},{"key":"4353_CR69","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1177\/001316446002000104","volume":"20","author":"J Cohen","year":"1960","unstructured":"Cohen J (1960) A coefficient of agreement for nominal scales. Educ Psychol Meas 20:37\u201346. https:\/\/doi.org\/10.1177\/001316446002000104","journal-title":"Educ Psychol Meas"},{"issue":"5","key":"4353_CR70","doi-asserted-by":"crossref","first-page":"04016003","DOI":"10.1061\/(ASCE)CP.1943-5487.0000553","volume":"30","author":"J Zhou","year":"2016","unstructured":"Zhou J, Li X, Mitri HS (2016) Classification of rockburst in underground projects: comparison of ten supervised learning methods. J Comput Civ Eng 30(5):04016003","journal-title":"J Comput Civ Eng"},{"key":"4353_CR71","doi-asserted-by":"crossref","first-page":"159","DOI":"10.2307\/2529310","volume":"33","author":"JR Landis","year":"1977","unstructured":"Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159\u2013174","journal-title":"Biometrics"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04353-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-019-04353-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04353-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,24]],"date-time":"2022-09-24T15:57:56Z","timestamp":1664035076000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-019-04353-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,25]]},"references-count":71,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2020,6]]}},"alternative-id":["4353"],"URL":"https:\/\/doi.org\/10.1007\/s00521-019-04353-z","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,25]]},"assertion":[{"value":"25 March 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 July 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 July 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}}]}}