{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T00:10:05Z","timestamp":1767139805774,"version":"build-2238731810"},"update-to":[{"DOI":"10.1007\/s00521-012-0955-9","type":"retraction","label":"Retraction","source":"retraction-watch","updated":{"date-parts":[[2013,8,1]],"date-time":"2013-08-01T00:00:00Z","timestamp":1375315200000},"record-id":"18693"}],"reference-count":23,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2012,5,11]],"date-time":"2012-05-11T00:00:00Z","timestamp":1336694400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2013,8]]},"DOI":"10.1007\/s00521-012-0955-9","type":"journal-article","created":{"date-parts":[[2012,5,9]],"date-time":"2012-05-09T21:31:43Z","timestamp":1336599103000},"page":"565-565","source":"Crossref","is-referenced-by-count":9,"title":["RETRACTED ARTICLE: Combining artificial neural network and unified particle swarm optimization for oil flow rate prediction: case study"],"prefix":"10.1007","volume":"23","author":[{"given":"Mohammad Ali","family":"Ahmadi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seyed Reza","family":"Shadizadeh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arash","family":"Goudarzi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2012,5,11]]},"reference":[{"key":"955_CR1","unstructured":"Allen TO, Roberts AP (1993) Production operations, vol 1, well compilations, work over, and stimulation. OGCI and Petro Skills Publications TULSA, Oklahoma. 4th edn, Chap. 9, pp 20\u201327"},{"key":"955_CR2","doi-asserted-by":"crossref","unstructured":"Balan B, Mohaghegh S, Ameri S (1995) State-of-the-art in permeability determination from well log data: part I-a comparative study, model development. In: SPE eastern regional conference and exhibition, West Virginia, pp 17\u201321","DOI":"10.2118\/30978-MS"},{"key":"955_CR3","volume-title":"Neural fuzzy adaptive modeling and control","author":"M Brown","year":"1994","unstructured":"Brown M, Harris C (1994) Neural fuzzy adaptive modeling and control. Prentice-Hall, Englewood Cliffs, NJ"},{"key":"955_CR4","doi-asserted-by":"crossref","unstructured":"Coulibaly P, Baldwin CK (2005) Nonstationary hydrological time series forecasting using nonlinear dynamic methods. J Hydrol 307(1\u20134):164\u2013174","DOI":"10.1016\/j.jhydrol.2004.10.008"},{"key":"955_CR5","unstructured":"de Souto MCP, Yamazaki A, Ludernir TB (2002) Optimization of neural network weights and architecture for odor recognition using simulated annealing. Proceedings of 2002 international joint conference on neural networks, vol 1, pp 547\u2013552"},{"issue":"3","key":"955_CR6","first-page":"286","volume":"33","author":"JH Doveton","year":"1992","unstructured":"Doveton JH, Prensky SE (1992) Geological applications of wireline logs: a synopsis of developments and trends. Log Analyst 33(3):286\u2013303","journal-title":"Log Analyst"},{"key":"955_CR7","unstructured":"Eberhart RC, Kennedy J (1995) A new optimizer using particle swarm theory. In: Proceedings of 6th symposium micro machine and human science, IEEE Service Center 39\u201343"},{"key":"955_CR8","volume-title":"Computational intelligence PC tools","author":"RC Eberhart","year":"1996","unstructured":"Eberhart RC, Simpson P, Dobbins R (1996) Computational intelligence PC tools. Academic Press, London"},{"key":"955_CR9","unstructured":"Fueki M, Tanaka Y, Nishi T, Yamazaki D (1998) Development of a multiphase flow meter without radioactive source. Paper No: 8795-MS, Offshore Technology Conference, Houston, TX, 4\u20137 May 1998"},{"key":"955_CR10","doi-asserted-by":"crossref","unstructured":"Garcia-Pedrajas N, Hervas-Martinez C, Munoz-Perez J, COVNET (2003) A cooperative co evolutionary model for evolving artificial neural networks. IEEE Trans Neural Netw 14:575\u2013596","DOI":"10.1109\/TNN.2003.810618"},{"key":"955_CR11","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/0893-6080(89)90020-8","volume":"2","author":"K Hornick","year":"1989","unstructured":"Hornick K, Stinchcombe M, White H (1989) Multilayer feed forward networks are universal approximators. Neural Netw 2:359\u2013366","journal-title":"Neural Netw"},{"issue":"5","key":"955_CR12","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1016\/0893-6080(90)90005-6","volume":"3","author":"K Hornik","year":"1990","unstructured":"Hornik K, Stinchcombe M, White H (1990) Universal approximation of an unknown mapping and its derivatives using multilayer feed forward networks. Neural Netw 3(5):551\u2013560","journal-title":"Neural Netw"},{"key":"955_CR13","doi-asserted-by":"crossref","unstructured":"Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Proceedings of IEEE international conference on neural networks, vol IV, IEEE Service Center 1942\u20131948","DOI":"10.1109\/ICNN.1995.488968"},{"key":"955_CR14","first-page":"137","volume-title":"Computational intelligence: a dynamic system perspective","author":"MM Millonas","year":"1994","unstructured":"Millonas MM (1994) Swarms, phase transitions, and collective intelligence. In: Palaniswami M, Attikiouzel Y, Marks R, Fogel D, Fukuda T (eds) Computational intelligence: a dynamic system perspective. IEEE Press, New York, pp 137\u2013151"},{"key":"955_CR15","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/0022-1694(70)90255-6","volume":"10","author":"JE Nash","year":"1970","unstructured":"Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models I: a discussion of principles. J Hydrol 10:282\u2013290","journal-title":"J Hydrol"},{"key":"955_CR16","unstructured":"Parsopoulos KE, Vrahatis MN (2004) UPSO: a unified particle swarm optimization scheme. In: Lecture series on computer and computational sciences, vol 1, Proceedings of international conference computer methods in science and engineering (ICCMSE 2004), VSP International Science Publishers, Zeist, The Netherlands, pp 868\u2013873"},{"key":"955_CR17","unstructured":"Piers GE, Perkins J, Escott D (1987) A new flow meter for production logging and well testing. SPE 16819"},{"key":"955_CR18","unstructured":"Qul X, Feng J, Sun W (2008) Parallel genetic algorithm model based on AHP and neural networks for enterprise comprehensive business. IEEE international conference on intelligent information hiding and multimedia signal processing, pp 897\u2013900"},{"key":"955_CR19","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1016\/S0098-1354(02)00148-5","volume":"26","author":"R Rallo","year":"2002","unstructured":"Rallo R, Ferre-Gin J, Arenas A, Giralt F (2002) Neural virtual sensor for the inferential prediction of product quality from process variables. Comput Chem Eng 26:1735\u20131754","journal-title":"Comput Chem Eng"},{"key":"955_CR20","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1109\/72.248452","volume":"4","author":"R Reed","year":"1993","unstructured":"Reed R (1993) Pruning algorithms-a survey. IEEE Trans Neural Netw 4:740\u2013747","journal-title":"IEEE Trans Neural Netw"},{"key":"955_CR21","doi-asserted-by":"crossref","unstructured":"Slater SG, Paterson AMcK, Marshall MF, Amerada Hess (UK) Limited (1997) The development and use of a subsea multiphase flow meter on the UK south Scott field. Paper No. 8549-MS, Offshore Technology Conference, 5\u20138 May 1997, Houston, TX","DOI":"10.4043\/8549-MS"},{"key":"955_CR22","doi-asserted-by":"crossref","unstructured":"Tang P, Xi Z (2008) The research on BP neural network model based on guaranteed convergence particle swarm optimization. In: Second international symposium on intelligent information technology application, IITA '08, Shanghai","DOI":"10.1109\/IITA.2008.111"},{"key":"955_CR23","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1016\/S0020-0190(02)00447-7","volume":"85","author":"IC Trelea","year":"2003","unstructured":"Trelea IC (2003) The particle swarm optimization algorithm: convergence analysis and parameter selection. Info Proc Lett 85:317\u2013325","journal-title":"Info Proc Lett"}],"updated-by":[{"DOI":"10.1007\/s00521-012-0955-9","type":"retraction","label":"Retraction","source":"retraction-watch","updated":{"date-parts":[[2013,8,1]],"date-time":"2013-08-01T00:00:00Z","timestamp":1375315200000},"record-id":"18693"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-012-0955-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-012-0955-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-012-0955-9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,28]],"date-time":"2019-06-28T09:02:36Z","timestamp":1561712556000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-012-0955-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,5,11]]},"references-count":23,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2013,8]]}},"alternative-id":["955"],"URL":"https:\/\/doi.org\/10.1007\/s00521-012-0955-9","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2012,5,11]]}}}