{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T13:43:26Z","timestamp":1772027006879,"version":"3.50.1"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2018,5,11]],"date-time":"2018-05-11T00:00:00Z","timestamp":1525996800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2018,5,11]],"date-time":"2018-05-11T00:00:00Z","timestamp":1525996800000},"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":["Neural Comput & Applic"],"published-print":{"date-parts":[[2019,5,3]]},"DOI":"10.1007\/s00521-018-3533-y","type":"journal-article","created":{"date-parts":[[2018,5,11]],"date-time":"2018-05-11T07:15:53Z","timestamp":1526022953000},"page":"1275-1300","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":42,"title":["RETRACTED ARTICLE: EoT-driven hybrid ambient assisted living framework with na\u00efve Bayes\u2013firefly algorithm"],"prefix":"10.1007","volume":"31","author":[{"given":"Mohammed K.","family":"Hassan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ali I.","family":"El Desouky","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mahmoud M.","family":"Badawy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amany M.","family":"Sarhan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6347-8368","authenticated-orcid":false,"given":"Mohamed","family":"Elhoseny","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M.","family":"Gunasekaran","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,5,11]]},"reference":[{"key":"3533_CR1","doi-asserted-by":"publisher","first-page":"579","DOI":"10.1109\/JBHI.2012.2234129","volume":"17","author":"P Rashidi","year":"2013","unstructured":"Rashidi P, Mihailidis A (2013) A survey on ambient-assisted living tools for older adults. IEEE J Biomed Heal Inform 17:579\u2013590. https:\/\/doi.org\/10.1109\/JBHI.2012.2234129","journal-title":"IEEE J Biomed Heal Inform"},{"key":"3533_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1978802.1978815","volume":"43","author":"F Sadri","year":"2011","unstructured":"Sadri F (2011) Ambient intelligence: a survey. ACM Comput Surv 43:1\u201366. https:\/\/doi.org\/10.1145\/1978802.1978815","journal-title":"ACM Comput Surv"},{"key":"3533_CR3","doi-asserted-by":"publisher","first-page":"2305","DOI":"10.3233\/JIFS-17348","volume":"33","author":"M Elhoseny","year":"2017","unstructured":"Elhoseny M, Shehab A, Yuan X (2017) Optimizing robot path in dynamic environments using genetic algorithm and Bezier curve. J Intell Fuzzy Syst 33:2305\u20132316","journal-title":"J Intell Fuzzy Syst"},{"key":"3533_CR4","doi-asserted-by":"crossref","unstructured":"Dubey H, Monteiro A, Constant N, et al (2017) Fog computing in medical internet-of-things: architecture, implementation, and applications. In: Handbook of large-scale distributed computing in smart healthcare. Springer, Berlin, pp 281\u2013321","DOI":"10.1007\/978-3-319-58280-1_11"},{"key":"3533_CR5","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.pmcj.2011.01.004","volume":"8","author":"J Ye","year":"2012","unstructured":"Ye J, Dobson S, McKeever S (2012) Situation identification techniques in pervasive computing: a review. Pervasive Mob Comput 8:36\u201366","journal-title":"Pervasive Mob Comput"},{"key":"3533_CR6","doi-asserted-by":"publisher","unstructured":"Elhoseny M, Ramirez-Gonzalez G, Abu-Elnasr OM, et al (2018) Secure medical data transmission model for IoT-based healthcare systems. IEEE Access pp 1\u20131. https:\/\/doi.org\/10.1109\/access.2018.2817615","DOI":"10.1109\/access.2018.2817615"},{"key":"3533_CR7","doi-asserted-by":"publisher","unstructured":"Sarker VK, Jiang M, Gia TN, et al (2017) Portable multipurpose bio-signal acquisition and wireless streaming device for wearables. In: SAS 2017\u20142017 IEEE Sensors Applications Symposium pp 3\u20138. https:\/\/doi.org\/10.1109\/sas.2017.7894053","DOI":"10.1109\/sas.2017.7894053"},{"key":"3533_CR8","doi-asserted-by":"publisher","first-page":"605","DOI":"10.1147\/sj.443.0605","volume":"44","author":"PL Emiliani","year":"2005","unstructured":"Emiliani PL, Stephanidis C (2005) Universal access to ambient intelligence environments: opportunities and challenges for people with disabilities. IBM Syst J 44:605\u2013619. https:\/\/doi.org\/10.1147\/sj.443.0605","journal-title":"IBM Syst J"},{"key":"3533_CR9","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1016\/j.future.2013.07.009","volume":"35","author":"A Forkan","year":"2014","unstructured":"Forkan A, Khalil I, Tari Z (2014) CoCaMAAL: a cloud-oriented context-aware middleware in ambient assisted living. Futur Gener Comput Syst 35:114\u2013127. https:\/\/doi.org\/10.1016\/j.future.2013.07.009","journal-title":"Futur Gener Comput Syst"},{"key":"3533_CR10","doi-asserted-by":"publisher","unstructured":"Forkan A, Khalil I, Ibaida A, Tari Z (2015) BDCaM: big data for context-aware monitoring\u2013a personalized knowledge discovery framework for assisted healthcare. IEEE Trans Cloud Comput pp 1\u20131. https:\/\/doi.org\/10.1109\/tcc.2015.2440269","DOI":"10.1109\/tcc.2015.2440269"},{"key":"3533_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2018.02.032","author":"MK Hassan","year":"2018","unstructured":"Hassan MK, El Desouky AI, Elghamrawy SM, Sarhan AM (2018) Intelligent hybrid remote patient-monitoring model with cloud-based framework for knowledge discovery. Comput Electr Eng. https:\/\/doi.org\/10.1016\/j.compeleceng.2018.02.032","journal-title":"Comput Electr Eng"},{"key":"3533_CR12","doi-asserted-by":"crossref","unstructured":"Elhoseny M, Abdelaziz A, Salama AS, et al (2018) A hybrid model of Internet of Things and cloud computing to manage big data in health services applications. Futur Gener Comput Syst (in press)","DOI":"10.1016\/j.future.2018.03.005"},{"key":"3533_CR13","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-017-0659-1","author":"A Darwish","year":"2017","unstructured":"Darwish A, Hassanien AE, Elhoseny M et al (2017) The impact of the hybrid platform of internet of things and cloud computing on healthcare systems: opportunities, challenges, and open problems. J Ambient Intell Humaniz Comput. https:\/\/doi.org\/10.1007\/s12652-017-0659-1","journal-title":"J Ambient Intell Humaniz Comput"},{"key":"3533_CR14","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1109\/MCOM.2017.1600374CM","volume":"55","author":"JH Abawajy","year":"2017","unstructured":"Abawajy JH, Hassan MM (2017) Federated internet of things and cloud computing pervasive patient health monitoring system. IEEE Commun Mag 55:48\u201353. https:\/\/doi.org\/10.1109\/MCOM.2017.1600374CM","journal-title":"IEEE Commun Mag"},{"key":"3533_CR15","doi-asserted-by":"crossref","unstructured":"Andriopoulou F, Dagiuklas T, Orphanoudakis T (2017) Integrating IoT and fog computing for healthcare service delivery. In: Components and services for IoT platforms. Springer, Berlin, pp 213\u2013232","DOI":"10.1007\/978-3-319-42304-3_11"},{"key":"3533_CR16","doi-asserted-by":"crossref","unstructured":"Masouros D, Bakolas I, Tsoutsouras V, et al (2017) From edge to cloud: design and implementation of a healthcare Internet of Things infrastructure. In: 2017 27th international symposium on power and timing modeling, optimization and simulation (PATMOS), pp 1\u20136","DOI":"10.1109\/PATMOS.2017.8106984"},{"key":"3533_CR17","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1023\/A:1007465528199","volume":"29","author":"N Friedman","year":"1997","unstructured":"Friedman N, Geiger D, Goldszmidt M et al (1997) Bayesian network classifiers *. Mach Learn 29:131\u2013163. https:\/\/doi.org\/10.1023\/A:1007465528199","journal-title":"Mach Learn"},{"key":"3533_CR18","doi-asserted-by":"crossref","unstructured":"Webb GI (2011) Na\u00efve bayes. In: Encyclopedia of machine learning. Springer, Berlin, pp 713\u2013714","DOI":"10.1007\/978-0-387-30164-8_576"},{"key":"3533_CR19","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1146\/annurev.ento.53.103106.093346","volume":"53","author":"SM Lewis","year":"2008","unstructured":"Lewis SM, Cratsley CK (2008) Flash signal evolution, mate choice, and predation in fireflies. Annu Rev Entomol 53:293\u2013321. https:\/\/doi.org\/10.1146\/annurev.ento.53.103106.093346","journal-title":"Annu Rev Entomol"},{"key":"3533_CR20","doi-asserted-by":"publisher","first-page":"725","DOI":"10.1128\/MCB.7.2.725","volume":"7","author":"JR de Wet","year":"1987","unstructured":"de Wet JR, Wood KV, DeLuca M et al (1987) Firefly luciferase gene: structure and expression in mammalian cells. Mol Cell Biol 7:725\u2013737. https:\/\/doi.org\/10.1128\/MCB.7.2.725","journal-title":"Mol Cell Biol"},{"key":"3533_CR21","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.swevo.2013.06.001","volume":"13","author":"I Fister","year":"2013","unstructured":"Fister I, Yang XS, Brest J (2013) A comprehensive review of firefly algorithms. Swarm Evol Comput 13:34\u201346. https:\/\/doi.org\/10.1016\/j.swevo.2013.06.001","journal-title":"Swarm Evol Comput"},{"key":"3533_CR22","doi-asserted-by":"crossref","unstructured":"Yang XS (2009) Firefly algorithms for multimodal optimization. In: Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in Bioinformatics), pp 169\u2013178","DOI":"10.1007\/978-3-642-04944-6_14"},{"key":"3533_CR23","doi-asserted-by":"publisher","first-page":"1263","DOI":"10.1109\/TKDE.2008.239","volume":"21","author":"H He","year":"2009","unstructured":"He H, Garcia EA (2009) Learning from imbalanced data. IEEE Trans Knowl Data Eng 21:1263\u20131284. https:\/\/doi.org\/10.1109\/TKDE.2008.239","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"3533_CR24","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1016\/j.ins.2013.07.007","volume":"250","author":"V L\u00f3pez","year":"2013","unstructured":"L\u00f3pez V, Fern\u00e1ndez A, Garc\u00eda S et al (2013) An insight into classification with imbalanced data: empirical results and current trends on using data intrinsic characteristics. Inf Sci (Ny) 250:113\u2013141. https:\/\/doi.org\/10.1016\/j.ins.2013.07.007","journal-title":"Inf Sci (Ny)"},{"key":"3533_CR25","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1111\/j.0824-7935.2004.t01-1-00228.x","volume":"20","author":"A Estabrooks","year":"2004","unstructured":"Estabrooks A, Jo T, Japkowicz N (2004) A multiple resampling method for learning from imbalanced data sets. Comput Intell 20:18\u201336. https:\/\/doi.org\/10.1111\/j.0824-7935.2004.t01-1-00228.x","journal-title":"Comput Intell"},{"key":"3533_CR26","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1109\/TKDE.2002.1000348","volume":"14","author":"KM Ting","year":"2002","unstructured":"Ting KM (2002) An instance-weighting method to induce cost-sensitive trees. IEEE Trans Knowl Data Eng 14:659\u2013665. https:\/\/doi.org\/10.1109\/TKDE.2002.1000348","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"3533_CR27","unstructured":"Elkan C (2001) The foundations of cost-sensitive learning. In: IJCAI international joint conference on artificial intelligence, pp 973\u2013978"},{"key":"3533_CR28","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1007\/978-3-540-30115-8_7","volume":"3201","author":"R Akbani","year":"2004","unstructured":"Akbani R, Kwek S, Japkowicz N (2004) Applying support vector machines to imbalanced datasets. Lnai 3201:39\u201350. https:\/\/doi.org\/10.1007\/978-3-540-30115-8_7","journal-title":"Lnai"},{"key":"3533_CR29","doi-asserted-by":"publisher","first-page":"3358","DOI":"10.1016\/j.patcog.2007.04.009","volume":"40","author":"Y Sun","year":"2007","unstructured":"Sun Y, Kamel MS, Wong AKC, Wang Y (2007) Cost-sensitive boosting for classification of imbalanced data. Pattern Recognit 40:3358\u20133378. https:\/\/doi.org\/10.1016\/j.patcog.2007.04.009","journal-title":"Pattern Recognit"},{"key":"3533_CR30","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1109\/TSMCB.2008.2002909","volume":"39","author":"Y Tang","year":"2009","unstructured":"Tang Y, Zhang YQ, Chawla NV (2009) SVMs modeling for highly imbalanced classification. IEEE Trans Syst Man Cybern Part B Cybern 39:281\u2013288. https:\/\/doi.org\/10.1109\/TSMCB.2008.2002909","journal-title":"IEEE Trans Syst Man Cybern Part B Cybern"},{"key":"3533_CR31","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1016\/j.knosys.2015.04.022","volume":"85","author":"JF D\u00edez-Pastor","year":"2015","unstructured":"D\u00edez-Pastor JF, Rodr\u00edguez JJ, Garc\u00eda-Osorio C, Kuncheva LI (2015) Random balance: ensembles of variable priors classifiers for imbalanced data. Knowl-Based Syst 85:96\u2013111. https:\/\/doi.org\/10.1016\/j.knosys.2015.04.022","journal-title":"Knowl-Based Syst"},{"key":"3533_CR32","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1016\/j.neunet.2007.12.031","volume":"21","author":"MA Mazurowski","year":"2008","unstructured":"Mazurowski MA, Habas PA, Zurada JM et al (2008) Training neural network classifiers for medical decision making: the effects of imbalanced datasets on classification performance. Neural Netw 21:427\u2013436. https:\/\/doi.org\/10.1016\/j.neunet.2007.12.031","journal-title":"Neural Netw"},{"key":"3533_CR33","unstructured":"He H, Bai Y, Garcia EA, Li S (2008) ADASYN: adaptive synthetic sampling approach for imbalanced learning. In: Proceedings of the international joint conference on neural networks, pp 1322\u20131328"},{"key":"3533_CR34","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1613\/jair.953","volume":"16","author":"NV Chawla","year":"2002","unstructured":"Chawla NV, Bowyer KW, Hall LO, Kegelmeyer WP (2002) SMOTE: synthetic minority over-sampling technique. J Artif Intell Res 16:321\u2013357. https:\/\/doi.org\/10.1613\/jair.953","journal-title":"J Artif Intell Res"},{"key":"3533_CR35","doi-asserted-by":"crossref","unstructured":"Chawla NV (2009) Data mining for imbalanced datasets: an overview. In: Data mining and knowledge discovery handbook, pp 875\u2013886","DOI":"10.1007\/978-0-387-09823-4_45"},{"key":"3533_CR36","doi-asserted-by":"publisher","first-page":"6585","DOI":"10.1016\/j.eswa.2011.12.043","volume":"39","author":"V L\u00f3pez","year":"2012","unstructured":"L\u00f3pez V, Fern\u00e1ndez A, Moreno-Torres JG, Herrera F (2012) Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics. Expert Syst Appl 39:6585\u20136608. https:\/\/doi.org\/10.1016\/j.eswa.2011.12.043","journal-title":"Expert Syst Appl"},{"key":"3533_CR37","doi-asserted-by":"publisher","unstructured":"Li X, Li X, Wang Y, et al (2008) Learning query intent from regularized click graphs. In: Proceedings of the 31st annual international ACM SIGIR conference on research and development in information retrieval, 339\u2013346. https:\/\/doi.org\/10.1145\/1390334.1390393","DOI":"10.1145\/1390334.1390393"},{"key":"3533_CR38","unstructured":"Libelium Comunicaciones Distribuidas S.L. (2017) Mysignals hw\u2013ehealth and medical IoT development platform for arduino. http:\/\/www.my-signals.com\/#what-is-mysignals. Accessed 1 Jan 2017"},{"key":"3533_CR39","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TSMCC.2009.2032660","volume":"40","author":"A Pantelopoulos","year":"2010","unstructured":"Pantelopoulos A, Bourbakis NG (2010) A survey on wearable sensor-based systems for health monitoring and prognosis. IEEE Trans Syst Man Cybern Part C Appl Rev 40:1\u201312","journal-title":"IEEE Trans Syst Man Cybern Part C Appl Rev"},{"key":"3533_CR40","doi-asserted-by":"publisher","first-page":"3733","DOI":"10.1007\/s11277-017-4023-8","volume":"95","author":"M Elhoseny","year":"2017","unstructured":"Elhoseny M, Farouk A, Zhou N et al (2017) dynamic multi-hop clustering in a wireless sensor network: performance improvement. Wirel Pers Commun 95:3733\u20133753. https:\/\/doi.org\/10.1007\/s11277-017-4023-8","journal-title":"Wirel Pers Commun"},{"key":"3533_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2017.12.022","author":"W Elsayed","year":"2017","unstructured":"Elsayed W, Elhoseny M, Sabbeh S, Riad A (2017) Self-maintenance model for wireless sensor networks. Comput Electr Eng. https:\/\/doi.org\/10.1016\/j.compeleceng.2017.12.022","journal-title":"Comput Electr Eng"},{"key":"3533_CR42","doi-asserted-by":"crossref","unstructured":"Dementyev A, Hodges S, Taylor S, Smith J (2013) Power consumption analysis of Bluetooth Low Energy, ZigBee and ANT sensor nodes in a cyclic sleep scenario. In: 2013 IEEE international wireless symposium, IWS 2013","DOI":"10.1109\/IEEE-IWS.2013.6616827"},{"key":"3533_CR43","doi-asserted-by":"publisher","first-page":"2024","DOI":"10.1002\/sec.1459","volume":"9","author":"M Elhoseny","year":"2016","unstructured":"Elhoseny M, Yuan X, El-Minir HK, Riad AM (2016) An energy efficient encryption method for secure dynamic WSN. Secur Commun Networks 9:2024\u20132031. https:\/\/doi.org\/10.1002\/sec.1459","journal-title":"Secur Commun Networks"},{"key":"3533_CR44","doi-asserted-by":"publisher","first-page":"2194","DOI":"10.1109\/LCOMM.2014.2381226","volume":"19","author":"M Elhoseny","year":"2015","unstructured":"Elhoseny M, Yuan X, Yu Z et al (2015) Balancing energy consumption in heterogeneous wireless sensor networks using genetic algorithm. IEEE Commun Lett 19:2194\u20132197. https:\/\/doi.org\/10.1109\/LCOMM.2014.2381226","journal-title":"IEEE Commun Lett"},{"key":"3533_CR45","unstructured":"CubeSensors CubeSensors\u2014Feel BETTER (2018) https:\/\/cubesensors.com\/. Accessed 10 Feb 2018"},{"key":"3533_CR46","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1007\/s10922-016-9379-7","volume":"25","author":"X Yuan","year":"2017","unstructured":"Yuan X, Elhoseny M, El-Minir HK, Riad AM (2017) A genetic algorithm-based, dynamic clustering method towards improved WSN longevity. J Netw Syst Manag 25:21\u201346. https:\/\/doi.org\/10.1007\/s10922-016-9379-7","journal-title":"J Netw Syst Manag"},{"key":"3533_CR47","first-page":"539","volume-title":"Data Mining: Practical Machine Learning Tools and Techniques","author":"IH Witten","year":"2016","unstructured":"Witten IH, Frank E, Hall MA et al (2016) Data Mining: Practical Machine Learning Tools and Techniques, 4th edn. Kaufmann, Morgan, pp 539\u2013557","edition":"4"},{"key":"3533_CR48","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0158738","author":"E Emary","year":"2016","unstructured":"Emary E, Zawbaa HM (2016) Impact of chaos functions on modern swarm optimizers. PLoS ONE. https:\/\/doi.org\/10.1371\/journal.pone.0158738","journal-title":"PLoS ONE"},{"key":"3533_CR49","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1109\/51.932728","volume":"20","author":"GB Moody","year":"2001","unstructured":"Moody GB, Mark RG, Goldberger AL (2001) Physionet: a web-based resource for the study of physiologic signals. IEEE Eng Med Biol Mag 20:70\u201375","journal-title":"IEEE Eng Med Biol Mag"},{"key":"3533_CR50","unstructured":"de Castro Ferreira MAP (2016) SHRAM-Smart Heart Rate and Activity Measurement. University of Porto. https:\/\/repositorioaberto.up.pt\/bitstream\/10216\/84403\/2\/137861.pdf. Aaccessed 1 March 2017"},{"key":"3533_CR51","doi-asserted-by":"publisher","unstructured":"Tharwat A, Mahdi H, Elhoseny M, Hassanien AE (2018) Recognizing human activity in mobile crowdsensing environment using optimized k-NN algorithm. Expert Systems With Applications, 12 April 2018 (https:\/\/doi.org\/10.1016\/j.eswa.2018.04.017)","DOI":"10.1016\/j.eswa.2018.04.017"},{"key":"3533_CR52","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-018-3177-y","author":"AAR Hosseinabadi","year":"2018","unstructured":"Hosseinabadi AAR, Vahidi J, Saemi B, Sangaiah AK, Elhoseny M (2018) Extended genetic algorithm for solving open-shop scheduling problem. Soft Comput. https:\/\/doi.org\/10.1007\/s00500-018-3177-y","journal-title":"Soft Comput"},{"key":"3533_CR53","doi-asserted-by":"publisher","unstructured":"Tharwat A, Elhoseny M, Hassanien AE, Gabel T, Arun Kumar N (2018) Intelligent bezi\u00e9r curve-based path planning model using chaotic particle swarm optimization algorithm. In: Cluster Computing, Springer, March 2018, pp 1\u201322. (https:\/\/doi.org\/10.1007\/s10586-018-2360-3)","DOI":"10.1007\/s10586-018-2360-3"},{"key":"3533_CR54","doi-asserted-by":"publisher","unstructured":"El Aziz MA, Hemdan AM, Ewees AA, Elhoseny M, Shehab S, Hassanien AE, Xiong S (2017) Prediction of biochar yield using adaptive neuro-fuzzy inference system with particle swarm optimization. In: 2017 IEEE PES Power Africa conference, June 27\u201330, Accra-Ghana, IEEE, 2017, pp 115\u2013120. (https:\/\/doi.org\/10.1109\/powerafrica.2017.7991209)","DOI":"10.1109\/powerafrica.2017.7991209"},{"key":"3533_CR55","doi-asserted-by":"crossref","unstructured":"Ewees AA, El Aziz MA, Elhoseny M (2017) Social-spider optimization algorithm for improving ANFIS to predict biochar yield. In: 8th international conference on computing, communication and networking technologies (8ICCCNT), July 3\u20135, Delhi, India, IEEE, 2017","DOI":"10.1109\/ICCCNT.2017.8203950"}],"updated-by":[{"DOI":"10.1007\/s00521-024-10093-6","type":"retraction","label":"Retraction","source":"publisher","updated":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T00:00:00Z","timestamp":1721174400000}}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-018-3533-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-018-3533-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-018-3533-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T06:04:02Z","timestamp":1721196242000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-018-3533-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,5,11]]},"references-count":55,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2019,5,3]]}},"alternative-id":["3533"],"URL":"https:\/\/doi.org\/10.1007\/s00521-018-3533-y","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,5,11]]},"assertion":[{"value":"14 March 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 May 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 May 2018","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 July 2024","order":4,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Correction","order":5,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"This article has been retracted. Please see the Retraction Notice for more detail:","order":6,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"https:\/\/doi.org\/10.1007\/s00521-024-10093-6","URL":"https:\/\/doi.org\/10.1007\/s00521-024-10093-6","order":7,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"There is no conflict of interest between the authors to publish this manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}