{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:27:34Z","timestamp":1740122854560,"version":"3.37.3"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"34","license":[{"start":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T00:00:00Z","timestamp":1709769600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T00:00:00Z","timestamp":1709769600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-023-17880-8","type":"journal-article","created":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T07:02:31Z","timestamp":1709794951000},"page":"80565-80582","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["High-quality seismological recorded dataset analysis for the estimation of peak ground acceleration in Himalayas"],"prefix":"10.1007","volume":"83","author":[{"given":"Anurag","family":"Rana","sequence":"first","affiliation":[]},{"given":"Pankaj","family":"Vaidya","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5055-3645","authenticated-orcid":false,"given":"Yu-Chen","family":"Hu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,3,7]]},"reference":[{"key":"17880_CR1","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1785\/gssrl.78.1.57","volume":"78","author":"JE Ebel","year":"2007","unstructured":"Ebel JE, Chambers DW, Kafka AL, Baglivo JA (2007) NonPoissonian Earthquake clustering and the hidden Markov model as bases for Earthquake forecasting in California. Seismol Res Lett 78:57\u201365","journal-title":"Seismol Res Lett"},{"unstructured":"Jim\u00e9nez A., Posadas AM., Tiampo KF (2008) Describing seismic pattern dynamics by means of Ising Cellular Automata. Nonlinear Time series analysis in the geosciences: applications in climatology, geodynamics and solar-terrestrial physics 273\u2013290. https:\/\/scholar.google.com\/scholar?hl=zh-TW&as_sdt=0%2C5&q=describing+seismic+pattern+dynamics+by+means+of+ISing+cellular+automata+&btnG=#d=gs_cit&t=1709645682066&u=%2Fscholar%3Fq%3Dinfo%3AenCXc4QvOjsJ%3Ascholar.TW","key":"17880_CR2"},{"key":"17880_CR3","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1016\/j.tecto.2008.06.007","volume":"457","author":"YM Wu","year":"2008","unstructured":"Wu YM, Chen CC, Zhao L, Chang CH (2008) Seismicity characteristics before the 2003 Chengkung, Taiwan, Earthquake. Tectonophy 457:177\u2013182","journal-title":"Tectonophy"},{"key":"17880_CR4","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1080\/01490419.2011.547804","volume":"34","author":"VS Rani","year":"2011","unstructured":"Rani VS, Srivastava K, Srinagesh D, Dimri VP (2011) Spatial and temporal variations of b-value and fractal analysis for the Makran region. Mar Geod 34:77\u201382","journal-title":"Mar Geod"},{"issue":"23","key":"17880_CR5","doi-asserted-by":"publisher","first-page":"4099","DOI":"10.3923\/jas.2009.4099.4114","volume":"9","author":"A Zamani","year":"2009","unstructured":"Zamani A, Nedaei M, Boostani R (2009) Tectonic zoning of Iran based on self organizing map. J Appl Sci 9(23):4099\u20134114","journal-title":"J Appl Sci"},{"key":"17880_CR6","doi-asserted-by":"publisher","first-page":"2215","DOI":"10.1007\/s00531-012-0771-6","volume":"101","author":"MR Sorbi","year":"2012","unstructured":"Sorbi MR, Nilfouroushan F, Zamani A (2012) Seismicity patterns associated with the September 10th, 2008 Qeshm Earthquake, South Iran. Int J Earth Sci 101:2215\u20132223","journal-title":"Int J Earth Sci"},{"key":"17880_CR7","first-page":"298","volume":"72","author":"S Venkataraman","year":"2010","unstructured":"Venkataraman S (2010) A grid-based neural network framework for multimodal biometrics world academy of science. Eng Technol 72:298\u2013303","journal-title":"Eng Technol"},{"issue":"6\u20137","key":"17880_CR8","first-page":"683","volume":"33","author":"KC Luk","year":"2000","unstructured":"Luk KC, Ball JE, Sharma A (2000) An application of artificial neural networks for rainfall forecasting. Math Comput Model 33(6\u20137):683\u2013693","journal-title":"Math Comput Model"},{"key":"17880_CR9","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.atmosres.2011.06.013","volume":"102","author":"RP Shukla","year":"2011","unstructured":"Shukla RP, Tripathi KC, Pandey AC, Das IML (2011) Prediction of Indian summer monsoon rainfall using Nino Indices: a neural network approach. Atmos Res 102:99\u2013109","journal-title":"Atmos Res"},{"key":"17880_CR10","doi-asserted-by":"publisher","first-page":"10696","DOI":"10.1016\/j.eswa.2009.02.043","volume":"36","author":"GS Atsalakis","year":"2009","unstructured":"Atsalakis GS, Valavanis KP (2009) Forecasting stock market short-term trends using a neuro fuzzy based methodology. Expert Syst Appl 36:10696\u201310707","journal-title":"Expert Syst Appl"},{"issue":"8","key":"17880_CR11","doi-asserted-by":"publisher","first-page":"537","DOI":"10.21474\/IJAR01\/1244","volume":"4","author":"A Rana","year":"2016","unstructured":"Rana A, Kumar A, Sharma A (2016) Neural network radial basis function classifier for Earthquake data using aFOA. Int J Adv Res 4(8):537\u2013540","journal-title":"Int J Adv Res"},{"issue":"4","key":"17880_CR12","first-page":"394","volume":"5","author":"A Rana","year":"2014","unstructured":"Rana A, Sharma A (2014) Resolving set-streaming stream-shop scheduling in distributed system by mean of an a FOA. Int J Comput Sci Eng Technol 5(4):394\u2013403","journal-title":"Int J Comput Sci Eng Technol"},{"key":"17880_CR13","volume-title":"Introduction to artificial neural systems","author":"JM Zurada","year":"1992","unstructured":"Zurada JM (1992) Introduction to artificial neural systems. West Publishing Company, USA"},{"unstructured":"Shibli M (2011) A novel approach to predict earthquakes using adaptive neural fuzzy inference system and conservation of energy-angular momentum. Int J Comput Inf Syst Ind Manag Appl 3:371\u2013390.\u00a0https:\/\/mirlabs.org\/ijcisim\/regular_papers_2011\/Paper43.pdf","key":"17880_CR14"},{"issue":"2","key":"17880_CR15","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1007\/s10950-011-9270-7","volume":"16","author":"JV Farahani","year":"2012","unstructured":"Farahani JV, Zare M, Lucas C (2012) Adaptive neuro-fuzzy inference systems for semi-automatic discrimination between seismic events: a study in Tehran region. J Seismolog 16(2):291\u2013303","journal-title":"J Seismolog"},{"unstructured":"Cowan EJ, Beatson RK, Fright WR, McLennan TJ, Mitchell TJ (2002) Rapid geological modelling. In: Applied structural geology for mineral exploration and mining, international symposium,\u00a0pp 23\u201325","key":"17880_CR16"},{"key":"17880_CR17","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1016\/j.jksus.2011.05.002","volume":"24","author":"ASN Alarifi","year":"2012","unstructured":"Alarifi ASN, Alarifi NSN, Al-Humidan S (2012) Earthquakes magnitude predication using artificial neural network in northern Red Sea area. J King Saud Univ Sci 24:301\u2013313","journal-title":"J King Saud Univ Sci"},{"key":"17880_CR18","doi-asserted-by":"publisher","first-page":"1314","DOI":"10.1016\/j.asoc.2012.10.014","volume":"13","author":"J Reyes","year":"2013","unstructured":"Reyes J, Morales-Esteban A, Mart\u00ednez-\u00c1lvarez F (2013) Neural networks to predict Earthquakes in Chile. Appl Soft Comput 13:1314\u20131328","journal-title":"Appl Soft Comput"},{"key":"17880_CR19","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1007\/s12517-020-5211-5","volume":"13","author":"A Shiuly","year":"2020","unstructured":"Shiuly A, Roy N, Sahu RB (2020) Prediction of peak ground acceleration for himalayan region using artificial neural network and genetic algorithm. Arab J Geosci 13:215. https:\/\/doi.org\/10.1007\/s12517-020-5211-5","journal-title":"Arab J Geosci"},{"key":"17880_CR20","doi-asserted-by":"publisher","first-page":"1885","DOI":"10.1007\/s11069-021-05121-w","volume":"111","author":"BK Bansal","year":"2022","unstructured":"Bansal BK, Singh SK, Suresh G et al (2022) A source and ground motion study of Earthquakes in and near Delhi (the National Capital Region), India. Nat Hazards 111:1885\u20131905. https:\/\/doi.org\/10.1007\/s11069-021-05121-w","journal-title":"Nat Hazards"},{"issue":"1\u20132","key":"17880_CR21","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/S0012-8252(02)00112-5","volume":"61","author":"J Douglas","year":"2003","unstructured":"Douglas J (2003) Earthquake ground motion estimation using strong-motion records: a review of equations for the estimation of peak ground acceleration and response spectral ordinates. Earth Sci Rev 61(1\u20132):43\u2013104. https:\/\/doi.org\/10.1016\/S0012-8252(02)00112-5. ISSN 0012-8252","journal-title":"Earth Sci Rev"},{"key":"17880_CR22","doi-asserted-by":"publisher","first-page":"1064","DOI":"10.1007\/s12517-022-10326-9","volume":"15","author":"R Jena","year":"2022","unstructured":"Jena R, Al-Amri A, Malulud KNA et al (2022) Estimating earthquake peak ground acceleration and intensity using short-time Fourier and wavelet transform techniques: a case study at Odisha, India. Arab J Geosci 15:1064. https:\/\/doi.org\/10.1007\/s12517-022-10326-9","journal-title":"Arab J Geosci"},{"issue":"109188","key":"17880_CR23","doi-asserted-by":"publisher","first-page":"0263","DOI":"10.1016\/j.tws.2022.109188","volume":"175","author":"M Zhang","year":"2022","unstructured":"Zhang M, Gao X, Xie X, Behnejad A, Parke G (2022) A method to directly estimate the dynamic failure peak ground acceleration of a single-layer reticulated dome. Thin-Walled Struct 175(109188):0263\u20138231. https:\/\/doi.org\/10.1016\/j.tws.2022.109188","journal-title":"Thin-Walled Struct"},{"issue":"1","key":"17880_CR24","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/j.gsf.2014.10.004","volume":"7","author":"M Gandomi","year":"2016","unstructured":"Gandomi M, Soltanpour M, Zolfaghari MR, Gandomi AH (2016) Prediction of peak ground acceleration of Iran\u2019s tectonic regions using a hybrid soft computing technique. Geosci Front 7(1):75\u201382. https:\/\/doi.org\/10.1016\/j.gsf.2014.10.004. ISSN 1674\u20139871","journal-title":"Geosci Front"},{"key":"17880_CR25","doi-asserted-by":"publisher","DOI":"10.3390\/app122111101","volume":"12","author":"P Zhang","year":"2022","unstructured":"Zhang P, Li X, Chen J (2022) Prediction method for mine earthquake in time sequence based on clustering analysis. Appl Sci 12:11101. https:\/\/doi.org\/10.3390\/app122111101","journal-title":"Appl Sci"},{"issue":"19","key":"17880_CR26","doi-asserted-by":"publisher","first-page":"5805","DOI":"10.1007\/s00500-016-2158-2","volume":"21","author":"S Saba","year":"2017","unstructured":"Saba S, Ahsan F, Mohsin S (2017) BAT-ANN based Earthquake prediction for Pakistan region. Soft Comput 21(19):5805\u20135813","journal-title":"Soft Comput"},{"issue":"11\u201312","key":"17880_CR27","doi-asserted-by":"publisher","first-page":"733","DOI":"10.1016\/S0965-9978(02)00081-9","volume":"33","author":"T Kerh","year":"2002","unstructured":"Kerh T, Chu D (2002) Neural networks approach and microtremor measurements in estimating peak ground acceleration due to strong motion. Adv Eng Softw 33(11\u201312):733\u2013742. https:\/\/doi.org\/10.1016\/S0965-9978(02)00081-9. ISSN 0965\u20139978","journal-title":"Adv Eng Softw"},{"key":"17880_CR28","doi-asserted-by":"publisher","first-page":"28419","DOI":"10.1007\/s11042-021-11001-z","volume":"80","author":"R Jain","year":"2021","unstructured":"Jain R, Nayyar A, Arora S et al (2021) A comprehensive analysis and prediction of Earthquake magnitude based on position and depth parameters using machine and deep learning models. Multimed Tools Appl 80:28419\u201328438. https:\/\/doi.org\/10.1007\/s11042-021-11001-z","journal-title":"Multimed Tools Appl"},{"key":"17880_CR29","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-022-13306-z","author":"Z Feng","year":"2022","unstructured":"Feng Z, Gonz\u00e1lez VA, Mutch C et al (2022) Exploring spiral narratives with immediate feedback in immersive virtual reality serious games for Earthquake emergency training. Multimedia Tools Appl. https:\/\/doi.org\/10.1007\/s11042-022-13306-z","journal-title":"Multimedia Tools Appl"},{"key":"17880_CR30","doi-asserted-by":"publisher","first-page":"3929","DOI":"10.1007\/s11042-019-7583-7","volume":"79","author":"K Ravikumar","year":"2020","unstructured":"Ravikumar K, RajivKannan A (2020) An enhancement of location estimation and Disaster event prediction using density based SPATIO-temporal clustering with GPS. Multimedia Tools Appl 79:3929\u20133941. https:\/\/doi.org\/10.1007\/s11042-019-7583-7","journal-title":"Multimedia Tools Appl"},{"doi-asserted-by":"publisher","unstructured":"Ali R, Kashani M, Akhani CV, Camp AH, Gandomi (2021) Chapter 18 - A neural network to predict spectral acceleration. In: Samui P, Dixon B, Bui DT (eds) Basics of computational geophysics. Elsevier, pp 335\u2013349.  https:\/\/doi.org\/10.1016\/B978-0-12-820513-6.00006-0. ISBN 9780128205136","key":"17880_CR31","DOI":"10.1016\/B978-0-12-820513-6.00006-0"},{"issue":"1","key":"17880_CR32","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/S0016-7169(14)71489-8","volume":"53","author":"P-E Adri\u00e1n","year":"2014","unstructured":"Adri\u00e1n P-E, G\u00f3mez R, Hong HP (2014) Use of neural network to predict the peak ground accelerations and pseudo spectral accelerations for Mexican Inslab and Interplate Earthquakes. Geof\u00edsica Int 53(1):39\u201357. https:\/\/doi.org\/10.1016\/S0016-7169(14)71489-8. ISSN 0016-7169","journal-title":"Geof\u00edsica Int"},{"key":"17880_CR33","doi-asserted-by":"publisher","first-page":"192","DOI":"10.1016\/j.asoc.2019.03.029","volume":"80","author":"A Derakhshani","year":"2019","unstructured":"Derakhshani A, Foruzan AH (2019) Predicting the principal strong ground motion parameters: a deep learning approach. Appl Soft Comput 80:192\u2013201. https:\/\/doi.org\/10.1016\/j.asoc.2019.03.029. ISSN 1568\u20134946","journal-title":"Appl Soft Comput"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17880-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-17880-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17880-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,9]],"date-time":"2024-10-09T12:09:04Z","timestamp":1728475744000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-17880-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,7]]},"references-count":33,"journal-issue":{"issue":"34","published-online":{"date-parts":[[2024,10]]}},"alternative-id":["17880"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-17880-8","relation":{},"ISSN":["1573-7721"],"issn-type":[{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2024,3,7]]},"assertion":[{"value":"21 September 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 September 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 December 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 March 2024","order":4,"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 that they do not have any conflict of interests that influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}