{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T07:53:51Z","timestamp":1761897231640},"reference-count":60,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2020,2,1]],"date-time":"2020-02-01T00:00:00Z","timestamp":1580515200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,2,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>In this paper, an approach for soil liquefaction evaluation using probabilistic method based on the world-wide SPT databases has been presented. In this respect, the parameters\u2019 uncertainties for liquefaction probability have been taken into account. A calibrated mapping function is developed using Bayes\u2019 theorem in order to capture the failure probabilities in the absence of the knowledge of parameter uncertainty. The probability models provide a simple, but also efficient decision-making tool in engineering design to quantitatively assess the liquefaction triggering thresholds. Within an extended framework of the first-order reliability method considering uncertainties, the reliability indices are determined through a well-performed meta-heuristic optimization algorithm called hybrid particle swarm optimization and genetic algorithm to find the most accurate liquefaction probabilities. Finally, the effects of the level of parameter uncertainty on liquefaction probability, as well as the quantification of the limit state model uncertainty in order to incorporate the correct model uncertainty, are investigated in the context of probabilistic reliability analysis. The results gained from the presented probabilistic model and the available models in the literature show the fact that the developed approach can be a robust tool for engineering design and analysis of liquefaction as a natural disaster.<\/jats:p>","DOI":"10.1093\/jcde\/qwaa011","type":"journal-article","created":{"date-parts":[[2020,2,4]],"date-time":"2020-02-04T20:08:58Z","timestamp":1580846938000},"page":"107-127","source":"Crossref","is-referenced-by-count":15,"title":["Computer-aided SPT-based reliability model for probability of liquefaction using hybrid PSO and GA"],"prefix":"10.1093","volume":"7","author":[{"given":"Maral","family":"Goharzay","sequence":"first","affiliation":[{"name":"Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Shahid Shahriari Square, Daneshjou Boulevard, Shahid Chamran Highway, 16589-53571 Tehran, Iran"}]},{"given":"Ali","family":"Noorzad","sequence":"first","affiliation":[{"name":"Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Shahid Shahriari Square, Daneshjou Boulevard, Shahid Chamran Highway, 16589-53571 Tehran, Iran"}]},{"given":"Ahmadreza Mahboubi","family":"Ardakani","sequence":"first","affiliation":[{"name":"Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Shahid Shahriari Square, Daneshjou Boulevard, Shahid Chamran Highway, 16589-53571 Tehran, Iran"}]},{"given":"Mostafa","family":"Jalal","sequence":"first","affiliation":[{"name":"Zachry Department of Civil Engineering, Texas A&M University, College Station, TX 77840, USA"}]}],"member":"286","published-online":{"date-parts":[[2020,3,19]]},"reference":[{"issue":"11","key":"2020042408254593300_bib1","doi-asserted-by":"crossref","first-page":"1015","DOI":"10.1061\/(ASCE)1090-0241(2000)126:11(1015)","article-title":"Liquefaction resistance of soils from shear-wave velocity","volume":"126","author":"Andrus","year":"2000","journal-title":"Journal of Geotechnical and 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