{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:55:57Z","timestamp":1777704957412,"version":"3.51.4"},"reference-count":34,"publisher":"SAGE Publications","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2024,4,18]]},"abstract":"<jats:p>In the present study, three hybrid models include support vector regression-salp swarm optimization (SVR-SSO), support vector regression-biogeography-based (SVR-BBO), and support vector regression-phasor particle swarm optimization (SVR- PPSO) was applied to forecast pond ash\u2019s CBR value modified with lime sludge (LS) and lime (LI). In the developed models, five variables were selected as inputs. It can result that the developed integrated models have R2 bigger than 0.9952. It means the agreement between observed and forecasted values by hybrid models is mainly similar to represent the highest accuracy. In both the training and testing stages, PSO-SVR results from better performance than the BBO-SVR model, with R2, RMSE, MAE, and PI equal to 0.9983, 0.6439, 0.3181, and 0.0081 for training data, and 0.9975, 0.7319, 0.4135, and 0.0141 for testing data, respectively. So, by considering the OBJ index, the OBJ value for PSO-SVR is 12.966, lower than BBO-SVR at 16.9957. Therefore, the PSO-SVR model outperforms another model to estimate the CBR of pond ash modified with LI and LS, consequently being recognized as the proposed model that makes it to be used for practical applications.<\/jats:p>","DOI":"10.3233\/jifs-220745","type":"journal-article","created":{"date-parts":[[2024,2,20]],"date-time":"2024-02-20T11:18:37Z","timestamp":1708427917000},"page":"8311-8327","source":"Crossref","is-referenced-by-count":0,"title":["Applying SVR-PPSO, SVR-SSO, and SVR-BBO to estimate california bearing capacity of stabilized pond ash using admixtures"],"prefix":"10.1177","volume":"46","author":[{"given":"Wei","family":"Teng","sequence":"first","affiliation":[{"name":"School of Computer Science and Software Engineering, University of Science and Technology Liaoning, Anshan, Liaoning, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Li","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan, Liaoning, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongxing","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Information Technology, Nanchang Vocational University, Nanchang, Jiangxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haojie","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Intelligent Construction, Luzhou Vocational and Technical College, Luzhou, Sichuan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-220745_ref1","first-page":"119","article-title":"Improvement of the mechanical and durability parameters of construction concrete of the Qotursuyi Spa","volume":"13.2","author":"Esmaeili Falak","year":"2020","journal-title":"Concrete Research"},{"key":"10.3233\/JIFS-220745_ref2","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1061\/(ASCE)0899-1561(2007)19:4(349)","article-title":"Compaction characteristics of pond ash","volume":"19.4","author":"Kumar Bera","year":"2007","journal-title":"Journal of Materials in Civil Engineering"},{"key":"10.3233\/JIFS-220745_ref4","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1061\/(ASCE)0733-9372(1996)122:10(935)","article-title":"Stabilization\/solidification of hazardous wastes using fly ash","volume":"122.10","author":"Parsa Jafar","year":"1996","journal-title":"Journal of Environmental Engineering"},{"key":"10.3233\/JIFS-220745_ref5","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1061\/(ASCE)0899-1561(2006)18:1(18)","article-title":"Tensile strength bearing ratio and slake durability of class F fly ash stabilized with lime and gypsum","volume":"18.1","author":"Ghosh Ambarish","year":"2006","journal-title":"Journal of Materials in Civil Engineering"},{"key":"10.3233\/JIFS-220745_ref6","first-page":"189","article-title":"Fly ash characterization with reference to geotechnical applications","volume":"84.6","author":"Pandian","year":"2004","journal-title":"Journal of the Indian Institute of Science"},{"key":"10.3233\/JIFS-220745_ref8","doi-asserted-by":"crossref","first-page":"757","DOI":"10.1061\/(ASCE)1090-0241(2007)133:7(757)","article-title":"Strength characteristics of class F fly ash modified with lime and gypsum","volume":"133.7","author":"Ghosh Ambarish","year":"2007","journal-title":"Journal of Geotechnical and Geoenvironmental Engineering"},{"key":"10.3233\/JIFS-220745_ref9","first-page":"23","article-title":"Class-F pond ash a potential highway construction material\u2013a review","volume":"43.8","author":"Suthar","year":"2015","journal-title":"Indian Highways"},{"key":"10.3233\/JIFS-220745_ref10","first-page":"30","article-title":"The use of fly ash and lime sludge as partial replacement of cement in mortar","volume":"4.1","author":"Sahu Vaishali","year":"2014","journal-title":"International Journal of Engineering and Technology Innovation"},{"key":"10.3233\/JIFS-220745_ref11","doi-asserted-by":"crossref","first-page":"2993","DOI":"10.1016\/j.biortech.2006.10.007","article-title":"Reduction of Pb and Zn bioavailable forms in metal polluted soils due to paper mill sludge addition: Effects on Pb and Zn transferability to barley","volume":"98.16","author":"Battaglia","year":"2007","journal-title":"Bioresource Technology"},{"key":"10.3233\/JIFS-220745_ref12","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1016\/j.envpol.2004.12.014","article-title":"Metal-contaminated soil remediation by means of paper mill sludges addition: chemical and ecotoxicological evaluation","volume":"136.3","author":"Calace","year":"2005","journal-title":"Environmental Pollution"},{"key":"10.3233\/JIFS-220745_ref13","doi-asserted-by":"crossref","first-page":"2093","DOI":"10.1016\/j.watres.2006.04.001","article-title":"A review of secondary sludge reduction technologies for the pulp and paper industry","volume":"40.11","author":"Mahmood Talat","year":"2006","journal-title":"Water Research"},{"key":"10.3233\/JIFS-220745_ref14","first-page":"51","article-title":"Physicochemical characteristics of lime sludge waste of paper mill and its impact on growth and production of rice","volume":"21.1","author":"Medhi","year":"2005","journal-title":"Journal of Industrial Pollution Control"},{"key":"10.3233\/JIFS-220745_ref15","first-page":"389","article-title":"A study of paper mill lime sludge for stabilization of village road sub-base","volume":"5.2","author":"Talukdar Kumar","year":"2015","journal-title":"Int J Emerg Technol Adv Eng"},{"key":"10.3233\/JIFS-220745_ref17","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1061\/(ASCE)MT.1943-5533.0000028","article-title":"Compaction characteristics and bearing ratio of pond ash stabilized with lime and phosphogypsum","volume":"22.4","author":"Ghosh Ambarish","year":"2010","journal-title":"Journal of Materials in Civil Engineering"},{"key":"10.3233\/JIFS-220745_ref19","first-page":"309","article-title":"Optimization of cost and mechanical properties of concrete with admixtures using MARS and PSO","volume":"26.4","author":"Benemaran Reza Sarkhani","year":"2020","journal-title":"Computers and Concrete, An International Journal"},{"key":"10.3233\/JIFS-220745_ref21","first-page":"1","article-title":"Evaluation of the bearing capacity of poor subgrade soils stabilized with waste marble powder according to curing time and freeze-thaw cycles","volume":"14.5","author":"Yorulmaz Aysegul","year":"2021","journal-title":"Arabian Journal of Geosciences"},{"key":"10.3233\/JIFS-220745_ref22","doi-asserted-by":"crossref","first-page":"3487","DOI":"10.2166\/ws.2020.241","article-title":"Automatic calibration of the groundwater simulation model with high parameter dimensionality using sequential uncertainty fitting approach","volume":"20.8","author":"Masoumi Fariborz","year":"2020","journal-title":"Water Supply"},{"key":"10.3233\/JIFS-220745_ref23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1680\/jgeen.20.00152","article-title":"Physical and numerical modelling of pile-stabilised saturated layered slopes","author":"Sarkhani Benemaran Reza","year":"2020","journal-title":"Proceedings of the Institution of Civil Engineers-Geotechnical Engineering"},{"key":"10.3233\/JIFS-220745_ref24","doi-asserted-by":"crossref","first-page":"04019007","DOI":"10.1061\/(ASCE)CR.1943-5495.0000188","article-title":"Predicting triaxial compressive strength and Young\u2019s modulus of frozen sand using artificial intelligence methods","volume":"33.3","author":"Esmaeili-Falak Mahzad","year":"2019","journal-title":"Journal of Cold Regions Engineering"},{"key":"10.3233\/JIFS-220745_ref25","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.enggeo.2018.09.018","article-title":"A new approach to modeling the behavior of frozen soils","volume":"246","author":"Nassr Ali","year":"2018","journal-title":"Engineering Geology"},{"key":"10.3233\/JIFS-220745_ref26","first-page":"454","article-title":"Undrained lateral load capacity of piles in clay using artificial neural network","volume":"33.8","author":"Das Sarat Kumar","year":"2006","journal-title":"Computers and Geotechnics"},{"key":"10.3233\/JIFS-220745_ref27","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1080\/1064119X.2010.514232","article-title":"Neural network model for predicting the resistance of driven piles","volume":"28.4","author":"Park","year":"2010","journal-title":"Marine Georesources and Geotechnology"},{"key":"10.3233\/JIFS-220745_ref28","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1016\/j.cageo.2012.09.003","article-title":"The prediction of the critical factor of safety of homogeneous finite slopes using neural networks and multiple regressions","volume":"51","author":"Erzin Yusuf","year":"2013","journal-title":"Computers & Geosciences"},{"key":"10.3233\/JIFS-220745_ref29","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1016\/j.cageo.2012.09.003","article-title":"The prediction of the critical factor of safety of homogeneous finite slopes using neural networks and multiple regressions","volume":"51","author":"Erzin Yusuf","year":"2013","journal-title":"Computers & Geosciences"},{"key":"10.3233\/JIFS-220745_ref30","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1016\/j.compgeo.2007.08.002","article-title":"Slope reliability analysis using a support vector machine","volume":"35.3","author":"Zhao Hong-bo","year":"2008","journal-title":"Computers and Geotechnics"},{"key":"10.3233\/JIFS-220745_ref31","first-page":"109","article-title":"Reducing prediction error by transforming input data for neural networks","volume":"14.2","author":"Shi Jonathan Jingsheng","year":"2000","journal-title":"Journal of Computing in Civil Engineering"},{"key":"10.3233\/JIFS-220745_ref32","first-page":"19","article-title":"Tunneling performance prediction using an integrated GIS and neural network","volume":"34.1","author":"Yoo Chungsik","year":"2007","journal-title":"Computers and Geotechnics"},{"key":"10.3233\/JIFS-220745_ref33","doi-asserted-by":"crossref","first-page":"6381","DOI":"10.1016\/j.eswa.2010.12.054","article-title":"Estimation of California bearing ratio by using soft computing systems","volume":"38.5","author":"Yildirim","year":"2011","journal-title":"Expert Systems with Applications"},{"key":"10.3233\/JIFS-220745_ref34","first-page":"3261","article-title":"Prediction of California bearing ratio of a soil stabilized with lime and quarry dust using artificial neural network","volume":"18","author":"Sabat Akshaya Kumar","year":"2013","journal-title":"Electronic Journal of Geotechnical Engineering"},{"key":"10.3233\/JIFS-220745_ref35","doi-asserted-by":"crossref","unstructured":"Suthar Manju , Praveen Aggarwal , Modeling CBR value using RF and M5P techniques, Mendel 25(1) (2019).","DOI":"10.13164\/mendel.2019.1.073"},{"key":"10.3233\/JIFS-220745_ref36","first-page":"1","article-title":"An intelligent approach for predicting the strength of geosynthetic-reinforced subgrade soil","author":"Raja Muhammad Nouman Amjad","year":"2021","journal-title":"International Journal of Pavement Engineering"},{"key":"10.3233\/JIFS-220745_ref37","doi-asserted-by":"crossref","first-page":"045036","DOI":"10.1088\/2631-8695\/ac3c9f","article-title":"Predicting CBR value of stabilized pond ash with lime and lime sludge using multivariate adaptive regression splines","volume":"3.4","author":"Xing-Xing Shen","year":"2021","journal-title":"Engineering Research Express"},{"key":"10.3233\/JIFS-220745_ref38","doi-asserted-by":"crossref","first-page":"702","DOI":"10.1109\/TEVC.2008.919004","article-title":"Biogeography-based optimization","volume":"12.6","author":"Simon Dan","year":"2008","journal-title":"IEEE transactions on Evolutionary Computation"},{"key":"10.3233\/JIFS-220745_ref42","first-page":"1","article-title":"Spatial mapping of groundwater springs potentiality using grid search-based and genetic algorithm-based support vector regression","author":"Al-Fugara","year":"2020","journal-title":"Geocarto International"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-220745","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:42:31Z","timestamp":1777455751000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-220745"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,18]]},"references-count":34,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.3233\/jifs-220745","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,18]]}}}