{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T14:41:24Z","timestamp":1776350484310,"version":"3.51.2"},"reference-count":50,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers &amp; Geosciences"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.cageo.2026.106147","type":"journal-article","created":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T07:23:58Z","timestamp":1772781838000},"page":"106147","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["A logistic gradient autonomous optimization numerical spiking neural membrane system with adaptive multi-mutation for sandstone pore segmentation"],"prefix":"10.1016","volume":"212","author":[{"given":"Zhuo","family":"Luo","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kai","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shiji","family":"Dai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Su","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changhui","family":"Yan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.cageo.2026.106147_bib1","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1016\/j.advwatres.2015.07.016","article-title":"Using synchrotron X-Ray microtomography to characterize the pore network of reservoir rocks: a case study on carbonates","volume":"95","author":"Arzilli","year":"2016","journal-title":"Adv. Water Resour."},{"key":"10.1016\/j.cageo.2026.106147_bib2","series-title":"2017 IEEE Congress on Evolutionary Computation (CEC), Donostia, San Sebasti\u00e1n, Spain","first-page":"372","article-title":"Ensemble sinusoidal differential covariance matrix adaptation with euclidean neighborhood for solving CEC2017 benchmark problems","author":"Awad","year":"2017"},{"key":"10.1016\/j.cageo.2026.106147_bib3","doi-asserted-by":"crossref","DOI":"10.1109\/TGRS.2023.3334867","article-title":"Ice-core Micro-CT image segmentation with deep learning and gaussian mixture model","volume":"61","author":"Bagherzadeh","year":"2023","journal-title":"IEEE Trans. Geosci. Rem. Sens."},{"key":"10.1016\/j.cageo.2026.106147_bib4","series-title":"2017 IEEE Congress on Evolutionary Computation (CEC), Donostia, San Sebasti\u00e1n, Spain","first-page":"1489","article-title":"A version of IPOP-CMA-ES algorithm with midpoint for CEC 2017 single objective bound constrained problems","author":"Biedrzycki","year":"2017"},{"key":"10.1016\/j.cageo.2026.106147_bib5","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1016\/j.cageo.2014.08.009","article-title":"Numerical modeling of fluid and electrical currents through geometries based on synchrotron X-Ray tomographic images of reservoir rocks using avizo and COMSOL","volume":"73","author":"Bird","year":"2014","journal-title":"Comput. Geosci."},{"issue":"2","key":"10.1016\/j.cageo.2026.106147_bib6","first-page":"227","article-title":"Research advances on reservoir pores","volume":"24","author":"Chen","year":"2013","journal-title":"Nat. Gas Geosci."},{"issue":"6","key":"10.1016\/j.cageo.2026.106147_bib7","first-page":"1547","article-title":"Performance analysis and improvement of logistic chaotic mapping","volume":"38","author":"Chen","year":"2016","journal-title":"J. Electron. Inf. Technol."},{"key":"10.1016\/j.cageo.2026.106147_bib8","doi-asserted-by":"crossref","first-page":"428","DOI":"10.1016\/j.ins.2023.01.026","article-title":"An optimization numerical spiking neural P system for solving constrained optimization problems","volume":"626","author":"Dong","year":"2023","journal-title":"Inf. Sci."},{"issue":"8","key":"10.1016\/j.cageo.2026.106147_bib9","doi-asserted-by":"crossref","DOI":"10.1142\/S0129065724500369","article-title":"An optimization numerical spiking neural membrane system with adaptive multi-mutation operators for brain tumor segmentation","volume":"34","author":"Dong","year":"2024","journal-title":"Int. J. Neural Syst."},{"issue":"6","key":"10.1016\/j.cageo.2026.106147_bib10","first-page":"1910","article-title":"Study of automatic extraction porosity using cast thin sections for carbonates","volume":"67","author":"Du","year":"2021","journal-title":"Geol. Rev."},{"key":"10.1016\/j.cageo.2026.106147_bib11","doi-asserted-by":"crossref","DOI":"10.1016\/j.conbuildmat.2023.133141","article-title":"Permeability evolution and pore characteristics of reactive powder concrete of drilling shaft with initial salt erosion damage","volume":"403","author":"Fang","year":"2023","journal-title":"Constr. Build. Mater."},{"issue":"2","key":"10.1016\/j.cageo.2026.106147_bib12","first-page":"115","article-title":"3D imaging and visualization technology of Micro pore structure in porous media","volume":"28","author":"Guan","year":"2009","journal-title":"Geol. Sci. Technol. Inf."},{"issue":"4","key":"10.1016\/j.cageo.2026.106147_bib13","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1007\/s41965-023-00133-w","article-title":"Cancer gene selection with adaptive optimization spiking neural P systems and hybrid classifiers","volume":"5","author":"Hu","year":"2023","journal-title":"J. Membr. Comput."},{"issue":"22","key":"10.1016\/j.cageo.2026.106147_bib14","doi-asserted-by":"crossref","first-page":"5742","DOI":"10.3390\/en17225742","article-title":"An approach for detecting faulty lines in a small-current, grounded system using learning spiking neural P systems with NLMS","volume":"17","author":"Hu","year":"2024","journal-title":"Energies"},{"key":"10.1016\/j.cageo.2026.106147_bib15","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.127416","article-title":"EPKO: enhanced pied kingfisher optimizer for numerical optimization and engineering problems","volume":"278","author":"Hu","year":"2025","journal-title":"Expert Syst. Appl."},{"issue":"2\u20133","key":"10.1016\/j.cageo.2026.106147_bib16","first-page":"279","article-title":"Spiking neural P systems","volume":"71","author":"Ionescu","year":"2006","journal-title":"Fundam. Inf."},{"issue":"23","key":"10.1016\/j.cageo.2026.106147_bib17","doi-asserted-by":"crossref","first-page":"7426","DOI":"10.3390\/ma16237426","article-title":"Investigation on three-dimensional void mesostructures and geometries in porous asphalt mixture based on computed tomography (CT) images and avizo","volume":"16","author":"Jing","year":"2023","journal-title":"Materials"},{"key":"10.1016\/j.cageo.2026.106147_bib18","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.eswa.2017.04.029","article-title":"Multilevel thresholding using grey wolf optimizer for image segmentation","volume":"86","author":"Khairuzzaman","year":"2017","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.cageo.2026.106147_bib19","series-title":"2017 IEEE Congress on Evolutionary Computation (CEC), Donostia, San Sebasti\u00e1n, Spain","first-page":"2397","article-title":"Teaching learning based optimization with focused learning and its performance on CEC2017 functions","author":"Kommadath","year":"2017"},{"issue":"2","key":"10.1016\/j.cageo.2026.106147_bib20","doi-asserted-by":"crossref","first-page":"1840003","DOI":"10.1142\/S0218348X18400030","article-title":"A new improved threshold segmentation method for scanning images of reservoir rocks considering pore fractal characteristics","volume":"26","author":"Lin","year":"2018","journal-title":"Fractals"},{"issue":"1","key":"10.1016\/j.cageo.2026.106147_bib21","doi-asserted-by":"crossref","DOI":"10.1515\/geo-2025-0791","article-title":"Fractal insights into permeability control by pore structure in tight sandstone reservoirs, heshui area, ordos basin","volume":"17","author":"Liu","year":"2025","journal-title":"Open Geosci."},{"key":"10.1016\/j.cageo.2026.106147_bib22","doi-asserted-by":"crossref","DOI":"10.1016\/j.petrol.2020.107400","article-title":"Sandstone surface relaxivity determined by NMR T2 distribution and digital rock simulation for permeability evaluation","volume":"193","author":"Lucas-Oliveira","year":"2020","journal-title":"J. Petrol. Sci. Eng."},{"key":"10.1016\/j.cageo.2026.106147_bib23","series-title":"2017 IEEE Congress on Evolutionary Computation (CEC), Donostia, San Sebasti\u00e1n, Spain","first-page":"145","article-title":"LSHADE with semi-parameter adaptation hybrid with CMA-ES for solving CEC 2017 benchmark problems","author":"Mohamed","year":"2017"},{"issue":"1","key":"10.1016\/j.cageo.2026.106147_bib24","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-021-90090-0","article-title":"High accuracy capillary network representation in digital rock reveals permeability scaling functions","volume":"11","author":"Neumann","year":"2021","journal-title":"Sci. Rep."},{"issue":"3","key":"10.1016\/j.cageo.2026.106147_bib25","first-page":"578","article-title":"Quantitative evaluation of pore connectivity with nuclear magnetic resonance and high pressure mercury injection: a case study of the lower section of Es3 in zhanhua sag","volume":"46","author":"Ning","year":"2017","journal-title":"J. China Inst. Min. Technol."},{"issue":"285\u2013296","key":"10.1016\/j.cageo.2026.106147_bib26","first-page":"23","article-title":"A threshold selection method from gray-level histograms","volume":"11","author":"Otsu","year":"1975","journal-title":"Automatica"},{"issue":"2","key":"10.1016\/j.cageo.2026.106147_bib27","doi-asserted-by":"crossref","first-page":"1281","DOI":"10.1007\/s11600-024-01416-1","article-title":"Petro-elastic model of the multiple pore-crack structure of carbonate rocks based on digital cores","volume":"73","author":"Pang","year":"2024","journal-title":"Acta Geophys."},{"issue":"1","key":"10.1016\/j.cageo.2026.106147_bib28","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1006\/jcss.1999.1693","article-title":"Computing with membranes","volume":"61","author":"P\u0103un","year":"2000","journal-title":"J. Comput. Syst. Sci."},{"issue":"1","key":"10.1016\/j.cageo.2026.106147_bib29","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/S0893-6080(98)00116-6","article-title":"On the momentum term in gradient descent learning algorithms","volume":"12","author":"Qian","year":"1999","journal-title":"Neural Netw."},{"key":"10.1016\/j.cageo.2026.106147_bib30","doi-asserted-by":"crossref","DOI":"10.3389\/feart.2025.1576484","article-title":"Multiscale pore\/throat characterization in tight sandstone formation with multi-threshold image segmentation algorithm","volume":"13","author":"Rongrong","year":"2025","journal-title":"Front. Earth Sci."},{"key":"10.1016\/j.cageo.2026.106147_bib31","series-title":"2017 IEEE Congress on Evolutionary Computation (CEC), Donostia, San Sebasti\u00e1n, Spain","first-page":"1350","article-title":"Multi-method based orthogonal experimental design algorithm for solving CEC2017 competition problems","author":"Sallam","year":"2017"},{"key":"10.1016\/j.cageo.2026.106147_bib32","doi-asserted-by":"crossref","DOI":"10.1016\/j.cageo.2021.104778","article-title":"Application of deep learning for semantic segmentation of sandstone thin sections","volume":"152","author":"Saxena","year":"2021","journal-title":"Comput. Geosci."},{"issue":"9","key":"10.1016\/j.cageo.2026.106147_bib33","first-page":"2103","article-title":"Research advances on stochastic gradient descent algorithms","volume":"47","author":"Shi","year":"2021","journal-title":"Acta Autom. Sin."},{"key":"10.1016\/j.cageo.2026.106147_bib34","doi-asserted-by":"crossref","DOI":"10.1016\/j.advwatres.2020.103801","article-title":"Computer vision and unsupervised machine learning for pore-scale structural of fractured media","volume":"147","author":"Singh","year":"2021","journal-title":"Adv. Water Resour."},{"key":"10.1016\/j.cageo.2026.106147_bib35","series-title":"2019 IEEE Congress on Evolutionary Computation (CEC)","first-page":"3126","article-title":"CEC real-parameter optimization competitions: progress from 2013 to 2018","author":"Skvorc","year":"2019"},{"issue":"4","key":"10.1016\/j.cageo.2026.106147_bib36","first-page":"7","article-title":"A survey of chaos and controlling chaos","volume":"14","author":"Su","year":"1996","journal-title":"Syst. Eng."},{"issue":"16","key":"10.1016\/j.cageo.2026.106147_bib37","doi-asserted-by":"crossref","first-page":"7178","DOI":"10.3390\/app14167178","article-title":"Innovative deep learning approaches for high-precision segmentation and characterization of sandstone pore structures in reservoirs","volume":"14","author":"Suo","year":"2024","journal-title":"Appl. Sci."},{"issue":"3","key":"10.1016\/j.cageo.2026.106147_bib38","doi-asserted-by":"crossref","first-page":"285","DOI":"10.2118\/99558-PA","article-title":"Analysis of chalk petrophysical properties by means of submicron-scale pore imaging and modeling","volume":"10","author":"Tomutsa","year":"2007","journal-title":"SPE Reservoir Eval. Eng."},{"issue":"4","key":"10.1016\/j.cageo.2026.106147_bib39","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1007\/s11770-020-0846-2","article-title":"Investigation of image segmentation effect on the accuracy of reconstructed digital core models of coquina carbonate","volume":"17","author":"Wang","year":"2020","journal-title":"Appl. Geophys."},{"issue":"18","key":"10.1016\/j.cageo.2026.106147_bib40","doi-asserted-by":"crossref","first-page":"961","DOI":"10.1007\/s12517-020-05928-0","article-title":"An investigation into pore structure fractal characteristics in tight oil reservoirs: a case study of the Triassic tight sandstone with ultra-low permeability in the ordos Basin, China","volume":"13","author":"Wang","year":"2020","journal-title":"Arabian J. Geosci."},{"key":"10.1016\/j.cageo.2026.106147_bib41","doi-asserted-by":"crossref","DOI":"10.1016\/j.geoen.2023.212207","article-title":"CSSRS: pore segmentation method of sandstone cast thin section images based on weak supervised learning","volume":"230","author":"Wang","year":"2023","journal-title":"Geoenergy Sci. Eng."},{"key":"10.1016\/j.cageo.2026.106147_bib42","article-title":"Multi-scale characterization of tight carbonate rocks based on digital cores","volume":"13","author":"Wang","year":"2025","journal-title":"Front. Earth Sci."},{"key":"10.1016\/j.cageo.2026.106147_bib43","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.petrol.2015.11.035","article-title":"An empirical approach of evaluating tight sandstone reservoir pore structure in the absence of NMR logs","volume":"137","author":"Xiao","year":"2016","journal-title":"J. Petrol. Sci. Eng."},{"issue":"4","key":"10.1016\/j.cageo.2026.106147_bib44","first-page":"45","article-title":"Analysis of the pore structure of shale gas reservoirs based on argon-ion milling SEM and ImageJ","volume":"38","author":"Xu","year":"2014","journal-title":"J. Northeast Petrol. Uni."},{"key":"10.1016\/j.cageo.2026.106147_bib45","series-title":"2024 IEEE Congress on Evolutionary Computation (CEC)","first-page":"1","article-title":"Tri-objective differential evolution with gradient information reused for constrained optimization","author":"Yang","year":"2024"},{"key":"10.1016\/j.cageo.2026.106147_bib46","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijepes.2025.110738","article-title":"Optimizing PID control for multi-model adaptive high-speed rail platform door systems with an improved metaheuristic approach","volume":"169","author":"Zhan","year":"2025","journal-title":"Int. J. Electr. Power Energy Syst."},{"issue":"5","key":"10.1016\/j.cageo.2026.106147_bib47","doi-asserted-by":"crossref","first-page":"1440006","DOI":"10.1142\/S0129065714400061","article-title":"AN optimization spiking neural P system for approximately solving combinatorial optimization problems","volume":"24","author":"Zhang","year":"2014","journal-title":"Int. J. Neural Syst."},{"key":"10.1016\/j.cageo.2026.106147_bib48","doi-asserted-by":"crossref","DOI":"10.1016\/j.petrol.2021.109675","article-title":"3D visualization of tectonic coal microstructure and quantitative characterization on topological connectivity of pore-fracture networks by Micro-CT","volume":"208","author":"Zhang","year":"2022","journal-title":"J. Petrol. Sci. Eng."},{"key":"10.1016\/j.cageo.2026.106147_bib49","doi-asserted-by":"crossref","DOI":"10.1016\/j.jgsce.2024.205343","article-title":"Interactive machine learning for segmenting pores of sandstone in computed tomography images","volume":"126","author":"Zhang","year":"2024","journal-title":"Gas Sci. Eng."},{"issue":"10","key":"10.1016\/j.cageo.2026.106147_bib50","doi-asserted-by":"crossref","first-page":"4285","DOI":"10.1016\/j.jrmge.2023.11.025","article-title":"Quantitatively characterizing sandy soil structure altered by MICP using multi-level thresholding segmentation algorithm","volume":"16","author":"Zi","year":"2024","journal-title":"J. Rock Mech. Geotech. Eng."}],"container-title":["Computers &amp; Geosciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0098300426000440?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0098300426000440?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T13:43:04Z","timestamp":1776346984000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0098300426000440"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":50,"alternative-id":["S0098300426000440"],"URL":"https:\/\/doi.org\/10.1016\/j.cageo.2026.106147","relation":{},"ISSN":["0098-3004"],"issn-type":[{"value":"0098-3004","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A logistic gradient autonomous optimization numerical spiking neural membrane system with adaptive multi-mutation for sandstone pore segmentation","name":"articletitle","label":"Article Title"},{"value":"Computers & Geosciences","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cageo.2026.106147","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"106147"}}