{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T10:15:14Z","timestamp":1775470514829,"version":"3.50.1"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"27","license":[{"start":{"date-parts":[[2023,7,20]],"date-time":"2023-07-20T00:00:00Z","timestamp":1689811200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,7,20]],"date-time":"2023-07-20T00:00:00Z","timestamp":1689811200000},"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":[[2023,9]]},"DOI":"10.1007\/s00521-023-08818-0","type":"journal-article","created":{"date-parts":[[2023,7,20]],"date-time":"2023-07-20T16:02:23Z","timestamp":1689868943000},"page":"20319-20338","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":43,"title":["A novel methodology for malicious traffic detection in smart devices using BI-LSTM\u2013CNN-dependent deep learning methodology"],"prefix":"10.1007","volume":"35","author":[{"given":"T.","family":"Anitha","sequence":"first","affiliation":[]},{"given":"S.","family":"Aanjankumar","sequence":"additional","affiliation":[]},{"given":"S.","family":"Poonkuntran","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9821-6146","authenticated-orcid":false,"given":"Anand","family":"Nayyar","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,7,20]]},"reference":[{"issue":"3","key":"8818_CR1","first-page":"1","volume":"16","author":"X Fan","year":"2023","unstructured":"Fan X, Yang R (2023) A network intrusion detection method based on improved Bi-LSTM in Internet of Things environment. Int J Inf Technol Syst Approach 16(3):1\u201314","journal-title":"Int J Inf Technol Syst Approach"},{"issue":"3","key":"8818_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3448614","volume":"21","author":"C Iwendi","year":"2021","unstructured":"Iwendi C, Rehman SU, Javed AR, Khan S, Srivastava G (2021) Sustainable security for the internet of things using artificial intelligence architectures. ACM Trans Internet Technology 21(3):1\u201322","journal-title":"ACM Trans Internet Technology"},{"issue":"3","key":"8818_CR3","doi-asserted-by":"publisher","first-page":"1785","DOI":"10.32604\/cmc.2020.010091","volume":"64","author":"C Du","year":"2020","unstructured":"Du C, Liu S, Si L, Guo Y, Jin T (2020) Using object detection network for malware detection and identification in network traffic packets. CMC-Comput Mater Continua 64(3):1785\u20131796","journal-title":"CMC-Comput Mater Continua"},{"issue":"2","key":"8818_CR4","doi-asserted-by":"publisher","first-page":"941","DOI":"10.32604\/cmc.2020.09802","volume":"64","author":"M Chen","year":"2020","unstructured":"Chen M, Wang X, He M, Jin L, Javeed K, Wang X (2020) A network traffic classification model based on metric learning. CMC-Comput Mater Continua 64(2):941\u2013959","journal-title":"CMC-Comput Mater Continua"},{"key":"8818_CR5","doi-asserted-by":"crossref","unstructured":"Li C, Wang J, Ye X (2018) Using a recurrent neural network and restricted Boltzmann machines for malicious traffic detection. Neuro Quantology 16(5)","DOI":"10.14704\/nq.2018.16.5.1391"},{"issue":"16","key":"8818_CR6","doi-asserted-by":"publisher","first-page":"3414","DOI":"10.3390\/app9163414","volume":"9","author":"RH Hwang","year":"2019","unstructured":"Hwang RH, Peng MC, Nguyen VL, Chang YL (2019) An LSTM-based deep learning approach for classifying malicious traffic at the packet level. Appl Sci 9(16):3414","journal-title":"Appl Sci"},{"key":"8818_CR7","doi-asserted-by":"crossref","unstructured":"Gao J (2022) Network intrusion detection method combining CNN and BiLSTM in cloud computing environment. In: Computational Intelligence and Neuroscience, 2022","DOI":"10.1155\/2022\/7272479"},{"key":"8818_CR8","doi-asserted-by":"publisher","first-page":"848","DOI":"10.1007\/s12559-018-9564-y","volume":"10","author":"BG Atli","year":"2018","unstructured":"Atli BG, Miche Y, Kalliola A, Oliver I, Holtmanns S, Lendasse A (2018) Anomaly-based intrusion detection using extreme learning machine and aggregation of network traffic statistics in probability space. Cognit Comput 10:848\u2013863","journal-title":"Cognit Comput"},{"key":"8818_CR9","doi-asserted-by":"publisher","first-page":"135771","DOI":"10.1016\/j.scitotenv.2019.135771","volume":"705","author":"J Ma","year":"2020","unstructured":"Ma J, Li Z, Cheng JC, Ding Y, Lin C, Xu Z (2020) Air quality prediction at new stations using spatially transferred bi-directional long short-term memory network. Sci Total Environ 705:135771","journal-title":"Sci Total Environ"},{"issue":"7","key":"8818_CR10","doi-asserted-by":"publisher","first-page":"983","DOI":"10.1093\/comjnl\/bxz064","volume":"63","author":"M Asad","year":"2020","unstructured":"Asad M, Asim M, Javed T, Beg MO, Mujtaba H, Abbas S (2020) Deepdetect: detection of distributed denial of service attacks using deep learning. Comput J 63(7):983\u2013994","journal-title":"Comput J"},{"issue":"5","key":"8818_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3460392","volume":"20","author":"AR Javed","year":"2021","unstructured":"Javed AR, Rehman SU, Khan MU, Alazab M, Khan HU (2021) Betalogger: smartphone sensor-based side-channel attack detection and text inference using language modeling and dense multilayer neural network. Trans Asian Low-Resour Lang Inf Process 20(5):1\u201317","journal-title":"Trans Asian Low-Resour Lang Inf Process"},{"key":"8818_CR12","doi-asserted-by":"publisher","first-page":"1301","DOI":"10.1016\/j.energy.2018.05.052","volume":"162","author":"L Peng","year":"2018","unstructured":"Peng L, Liu S, Liu R, Wang L (2018) Effective long short-term memory with differential evolution algorithm for electricity price prediction. Energy 162:1301\u20131314","journal-title":"Energy"},{"key":"8818_CR13","doi-asserted-by":"publisher","first-page":"56847","DOI":"10.1109\/ACCESS.2020.2978035","volume":"8","author":"R Vijayanand","year":"2020","unstructured":"Vijayanand R, Devaraj D (2020) A novel feature selection method using whale optimization algorithm and genetic operators for intrusion detection system in wireless mesh network. IEEE Access 8:56847\u201356854","journal-title":"IEEE Access"},{"key":"8818_CR14","doi-asserted-by":"publisher","first-page":"66408","DOI":"10.1109\/ACCESS.2021.3076264","volume":"9","author":"A Abbasi","year":"2021","unstructured":"Abbasi A, Javed AR, Chakraborty C, Nebhen J, Zehra W, Jalil Z (2021) ElStream: an ensemble learning approach for concept drift detection in dynamic social big data stream learning. IEEE Access 9:66408\u201366419","journal-title":"IEEE Access"},{"key":"8818_CR15","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1007\/s10509-013-1756-z","volume":"350","author":"EI Abouelmagd","year":"2014","unstructured":"Abouelmagd EI, Awad ME, Elzayat EMA, Abbas IA (2014) Reduction the secular solution to periodic solution in the generalized restricted three-body problem. Astrophys Space Sci 350:495\u2013505","journal-title":"Astrophys Space Sci"},{"issue":"2","key":"8818_CR16","doi-asserted-by":"publisher","first-page":"448","DOI":"10.1016\/j.jfranklin.2015.11.013","volume":"353","author":"B Du","year":"2016","unstructured":"Du B, Liu Y, Abbas IA (2016) Existence and asymptotic behavior results of periodic solution for discrete-time neutral-type neural networks. J Frankl Inst 353(2):448\u2013461","journal-title":"J Frankl Inst"},{"key":"8818_CR17","doi-asserted-by":"publisher","first-page":"101752","DOI":"10.1016\/j.cose.2020.101752","volume":"92","author":"SM Kasongo","year":"2020","unstructured":"Kasongo SM, Sun Y (2020) A deep learning method with wrapper based feature extraction for wireless intrusion detection system. Comput Secur 92:101752","journal-title":"Comput Secur"},{"issue":"8","key":"8818_CR18","doi-asserted-by":"publisher","first-page":"3801","DOI":"10.2166\/wcc.2021.460","volume":"12","author":"R Maddu","year":"2021","unstructured":"Maddu R, Vanga AR, Sajja JK, Basha G, Shaik R (2021) Prediction of land surface temperature of major coastal cities of India using bidirectional LSTM neural networks. J Water Climate Change 12(8):3801\u20133819","journal-title":"J Water Climate Change"},{"key":"8818_CR19","doi-asserted-by":"publisher","first-page":"409","DOI":"10.1016\/j.neucom.2015.11.046","volume":"177","author":"Y Liu","year":"2016","unstructured":"Liu Y, Liu W, Obaid MA, Abbas IA (2016) Exponential stability of Markovian jumping Cohen\u2013Grossberg neural networks with mixed mode-dependent time-delays. Neurocomputing 177:409\u2013415","journal-title":"Neurocomputing"},{"issue":"3","key":"8818_CR20","doi-asserted-by":"publisher","first-page":"1043","DOI":"10.1109\/TNSE.2019.2901994","volume":"7","author":"A Montieri","year":"2019","unstructured":"Montieri A, Ciuonzo D, Bovenzi G, Persico V, Pescap\u00e9 A (2019) A dive into the dark web: hierarchical traffic classification of anonymity tools. IEEE Trans Netw Sci Eng 7(3):1043\u20131054","journal-title":"IEEE Trans Netw Sci Eng"},{"key":"8818_CR21","doi-asserted-by":"crossref","unstructured":"Aanjankumar S, Poonkuntran S (2016) Peer-2-Peer Botnet manage SDT security algorithm. In: 2016 IEEE international conference on computational intelligence and computing research (ICCIC), pp 1\u20135. IEEE","DOI":"10.1109\/ICCIC.2016.7919661"},{"key":"8818_CR22","doi-asserted-by":"publisher","first-page":"58194","DOI":"10.1109\/ACCESS.2020.2982544","volume":"8","author":"M Hanselmann","year":"2020","unstructured":"Hanselmann M, Strauss T, Dormann K, Ulmer H (2020) CANet: an unsupervised intrusion detection system for high dimensional CAN bus data. IEEE Access 8:58194\u201358205","journal-title":"IEEE Access"},{"key":"8818_CR23","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.diin.2019.05.004","volume":"30","author":"E Fidalgo","year":"2019","unstructured":"Fidalgo E, Alegre E, Fern\u00e1ndez-Robles L, Gonz\u00e1lez-Castro V (2019) Classifying suspicious content in tor darknet through Semantic Attention Keypoint Filtering. Digit Investig 30:12\u201322","journal-title":"Digit Investig"},{"issue":"8","key":"8818_CR24","doi-asserted-by":"publisher","first-page":"e0273156","DOI":"10.1371\/journal.pone.0273156","volume":"17","author":"D Endalie","year":"2022","unstructured":"Endalie D, Haile G, Taye W (2022) Bi-directional long short-term memory-gated recurrent unit model for Amharic next word prediction. PLoS ONE 17(8):e0273156","journal-title":"PLoS ONE"},{"key":"8818_CR25","doi-asserted-by":"crossref","unstructured":"Imtiaz SI, ur Rehman S, Javed AR, Jalil Z, Liu X, Alnumay WS (2021) DeepAMD: detection and identification of Android malware using high-efficient Deep Artificial Neural Network. Future Gener Comput Syst 115:844\u2013856","DOI":"10.1016\/j.future.2020.10.008"},{"key":"8818_CR26","doi-asserted-by":"crossref","unstructured":"Soro F, Allegretta M, Mellia M, Drago I, Bertholdo LM (2020) Sensing the noise: uncovering communities in darknet traffic. In: 2020 Mediterranean communication and computer networking conference (MedComNet). IEEE, pp 1\u20138","DOI":"10.1109\/MedComNet49392.2020.9191555"},{"key":"8818_CR27","unstructured":"Thilakarathne NN, Kagita MK, Lanka D, Ahmad H (2020) Smart grid: a survey of architectural elements, machine learning and deep learning applications and future directions. arXiv preprint arXiv:2010.08094"},{"issue":"2","key":"8818_CR28","doi-asserted-by":"publisher","first-page":"1079","DOI":"10.1109\/TII.2020.2988870","volume":"17","author":"L Wang","year":"2020","unstructured":"Wang L, Mei H, Sheng VS (2020) Multilevel identification and classification analysis of Tor on mobile and PC platforms. IEEE Trans Ind Inf 17(2):1079\u20131088","journal-title":"IEEE Trans Ind Inf"},{"issue":"21","key":"8818_CR29","doi-asserted-by":"publisher","first-page":"16499","DOI":"10.1007\/s00500-020-04956-y","volume":"24","author":"S Aanjankumar","year":"2020","unstructured":"Aanjankumar S, Poonkuntran S (2020) An efficient soft computing approach for securing information over GAMEOVER Zeus Botnets with modified CPA algorithm. Soft Comput 24(21):16499\u201316507","journal-title":"Soft Comput"},{"key":"8818_CR30","doi-asserted-by":"crossref","unstructured":"Balasubramaniam S, Vijesh Joe C, Sivakumar TA, Prasanth A, Satheesh Kumar K, Kavitha V, Dhanaraj RK (2023) Optimization enabled deep learning-based DDoS attack detection in cloud computing. Int J Intell Syst","DOI":"10.1155\/2023\/2039217"},{"key":"8818_CR31","doi-asserted-by":"publisher","first-page":"100167","DOI":"10.1016\/j.iot.2020.100167","volume":"9","author":"RM Shukla","year":"2020","unstructured":"Shukla RM, Sengupta S (2020) Scalable and robust outlier detector using hierarchical clustering and long short-term memory (lstm) neural network for the internet of things. Internet Things 9:100167","journal-title":"Internet Things"},{"key":"8818_CR32","doi-asserted-by":"publisher","first-page":"34929","DOI":"10.1109\/ACCESS.2020.2973608","volume":"8","author":"I Dutt","year":"2020","unstructured":"Dutt I, Borah S, Maitra IK (2020) Immune system based intrusion detection system (IS-IDS): a proposed model. IEEE Access 8:34929\u201334941","journal-title":"IEEE Access"},{"issue":"10","key":"8818_CR33","doi-asserted-by":"publisher","first-page":"e4088","DOI":"10.1002\/ett.4088","volume":"33","author":"A Rehman Javed","year":"2022","unstructured":"Rehman Javed A, Jalil Z, Atif Moqurrab S, Abbas S, Liu X (2022) Ensemble adaboost classifier for accurate and fast detection of botnet attacks in connected vehicles. Trans Emerg Telecommun Technol 33(10):e4088","journal-title":"Trans Emerg Telecommun Technol"},{"key":"8818_CR34","doi-asserted-by":"crossref","unstructured":"ur Rehman S, Khaliq M, Imtiaz SI, Rasool A, Shafiq M, Javed AR, Bashir AK (2021) DIDDOS: an approach for detection and identification of Distributed Denial of Service (DDoS) cyberattacks using Gated Recurrent Units (GRU). Future Gener Comput Syst 118:453\u2013466","DOI":"10.1016\/j.future.2021.01.022"},{"key":"8818_CR35","doi-asserted-by":"crossref","unstructured":"Hwang RH, Peng MC, Huang CW (2019) Detecting IoT malicious traffic based on autoencoder and convolutional neural network. In: 2019 IEEE Globecom workshops (GC Wkshps). IEEE, pp 1\u20136","DOI":"10.1109\/GCWkshps45667.2019.9024425"},{"issue":"4","key":"8818_CR36","doi-asserted-by":"publisher","first-page":"314","DOI":"10.1177\/0361198119840611","volume":"2673","author":"J Yuan","year":"2019","unstructured":"Yuan J, Abdel-Aty M, Gong Y, Cai Q (2019) Real-time crash risk prediction using long short-term memory recurrent neural network. Transp Res Rec 2673(4):314\u2013326","journal-title":"Transp Res Rec"},{"key":"8818_CR37","doi-asserted-by":"crossref","unstructured":"Dong Y, Wang R, He J (2019) Real-time network intrusion detection system based on deep learning. In: 2019 IEEE 10th international conference on software engineering and service science (ICSESS). IEEE, pp 1\u20134","DOI":"10.1109\/ICSESS47205.2019.9040718"},{"key":"8818_CR38","doi-asserted-by":"crossref","unstructured":"Rajesh E, Basheer S, Dhanaraj RK, Yadav S, Kadry S, Khan MA, Cha JH (2022) Machine learning for online automatic prediction of common disease attributes using never-ending image learner. Diagnostics 13(1):5","DOI":"10.3390\/diagnostics13010095"},{"issue":"3","key":"8818_CR39","doi-asserted-by":"publisher","first-page":"662","DOI":"10.1109\/TDSC.2018.2804394","volume":"17","author":"A Montieri","year":"2018","unstructured":"Montieri A, Ciuonzo D, Aceto G, Pescap\u00e9 A (2018) Anonymity services tor, i2p, jondonym: classifying in the dark (web). IEEE Trans Dependable Secure Comput 17(3):662\u2013675","journal-title":"IEEE Trans Dependable Secure Comput"},{"key":"8818_CR40","doi-asserted-by":"crossref","unstructured":"Arulprakash A, Baalamurugan KM, Dhanaraj RK, Sampath Kumar K, Gupta P, Rehman S (2022) Aggregation technique using dynamic cross-propagation clustering algorithm in wireless body sensor networks. Wirel Commun Mobile Comput","DOI":"10.1155\/2022\/6102584"},{"key":"8818_CR41","doi-asserted-by":"crossref","unstructured":"Ahmed W, Shahzad F, Javed AR, Iqbal F, Ali L (2021) Whatsapp network forensics: discovering the ip addresses of suspects. In: 2021 11th IFIP international conference on new technologies, mobility and security (NTMS). IEEE, pp 1\u20137","DOI":"10.1109\/NTMS49979.2021.9432677"},{"key":"8818_CR42","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12984-020-00774-3","volume":"18","author":"M Ghislieri","year":"2021","unstructured":"Ghislieri M, Cerone GL, Knaflitz M, Agostini V (2021) Long short-term memory (LSTM) recurrent neural network for muscle activity detection. J Neuro Eng Rehabil 18:1\u201315","journal-title":"J Neuro Eng Rehabil"},{"key":"8818_CR43","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2021\/5589075","volume":"2021","author":"RL Abduljabbar","year":"2021","unstructured":"Abduljabbar RL, Dia H, Tsai PW (2021) Unidirectional and bidirectional LSTM models for short-term traffic prediction. J Adv Transp 2021:1\u201316","journal-title":"J Adv Transp"},{"key":"8818_CR44","doi-asserted-by":"crossref","unstructured":"Jeyaselvi M, Dhanaraj RK, Sathya M, Memon FH, Krishnasamy L, Dev K, Qureshi NMF (2023) A highly secured intrusion detection system for IoT using EXPSO-STFA feature selection for LAANN to detect attacks. Cluster Comput 26(1):559\u2013574","DOI":"10.1007\/s10586-022-03607-1"},{"issue":"1","key":"8818_CR45","doi-asserted-by":"publisher","first-page":"20","DOI":"10.3390\/info12010020","volume":"12","author":"F Gereme","year":"2021","unstructured":"Gereme F, Zhu W, Ayall T, Alemu D (2021) Combating fake news in \u201clow-resource\u201d languages: amharic fake news detection accompanied by resource crafting. Information 12(1):20","journal-title":"Information"},{"key":"8818_CR46","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1007\/s11235-020-00733-2","volume":"76","author":"A Basit","year":"2021","unstructured":"Basit A, Zafar M, Liu X, Javed AR, Jalil Z, Kifayat K (2021) A comprehensive survey of AI-enabled phishing attacks detection techniques. Telecommun Syst 76:139\u2013154","journal-title":"Telecommun Syst"},{"key":"8818_CR47","doi-asserted-by":"crossref","unstructured":"Basit A, Zafar M, Javed AR, Jalil Z (2020) A novel ensemble machine learning method to detect phishing attack. In: 2020 IEEE 23rd international multitopic conference (INMIC). IEEE, pp 1\u20135","DOI":"10.1109\/INMIC50486.2020.9318210"},{"key":"8818_CR48","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.neucom.2019.11.065","volume":"383","author":"R Biswas","year":"2020","unstructured":"Biswas R, Gonz\u00e1lez-Castro V, Fidalgo E, Alegre E (2020) Perceptual image hashing based on frequency dominant neighborhood structure applied to Tor domains recognition. Neurocomputing 383:24\u201338","journal-title":"Neurocomputing"},{"key":"8818_CR49","doi-asserted-by":"crossref","unstructured":"Berman A, Paul CL (2019) Making sense of darknet markets: automatic inference of semantic classifications from unconventional multimedia datasets. In: HCI for cybersecurity, privacy and trust: first international conference, HCI-CPT 2019, held as part of the 21st HCI international conference, HCII 2019, Orlando, FL, USA, July 26\u201331, 2019, proceedings 21. Springer, pp 230\u2013248","DOI":"10.1007\/978-3-030-22351-9_16"},{"issue":"2","key":"8818_CR50","doi-asserted-by":"publisher","first-page":"448","DOI":"10.1016\/j.gltp.2021.08.017","volume":"2","author":"TS Pooja","year":"2021","unstructured":"Pooja TS, Shrinivasacharya P (2021) Evaluating neural networks using Bi-Directional LSTM for network IDS (intrusion detection systems) in cyber security. Glob Transit Proc 2(2):448\u2013454","journal-title":"Glob Transit Proc"},{"key":"8818_CR51","doi-asserted-by":"publisher","first-page":"29575","DOI":"10.1109\/ACCESS.2020.2972627","volume":"8","author":"T Su","year":"2020","unstructured":"Su T, Sun H, Zhu J, Wang S, Li Y (2020) BAT: deep learning methods on network intrusion detection using NSL-KDD dataset. IEEE Access 8:29575\u201329585","journal-title":"IEEE Access"},{"key":"8818_CR52","doi-asserted-by":"crossref","unstructured":"Buldin ID, Ivanov NS (2020) Text classification of illegal activities on onion sites. In: 2020 IEEE conference of Russian young researchers in electrical and electronic engineering (EIConRus). IEEE, pp 245\u2013247","DOI":"10.1109\/EIConRus49466.2020.9039341"},{"issue":"2","key":"8818_CR53","first-page":"3","volume":"10","author":"A Nastu\u0142a","year":"2020","unstructured":"Nastu\u0142a A (2020) Dilemmas related to the functioning and growth of Darknet and the Onion Router network. J Sci Pap \u02bd\u02bdSoc Dev Secur\u2019\u2019 10(2):3\u201310","journal-title":"J Sci Pap \u02bd\u02bdSoc Dev Secur''"},{"issue":"3","key":"8818_CR54","doi-asserted-by":"publisher","first-page":"e2065","DOI":"10.1002\/nem.2065","volume":"29","author":"S Lagraa","year":"2019","unstructured":"Lagraa S, Chen Y, Fran\u00e7ois J (2019) Deep mining port scans from darknet. Int J Netw Manage 29(3):e2065","journal-title":"Int J Netw Manage"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08818-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-023-08818-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08818-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,30]],"date-time":"2023-08-30T00:13:11Z","timestamp":1693354391000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-023-08818-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,20]]},"references-count":54,"journal-issue":{"issue":"27","published-print":{"date-parts":[[2023,9]]}},"alternative-id":["8818"],"URL":"https:\/\/doi.org\/10.1007\/s00521-023-08818-0","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,20]]},"assertion":[{"value":"24 January 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 June 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 July 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflicts of interest to report regarding the present study.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}