{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T02:51:44Z","timestamp":1770346304746,"version":"3.49.0"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2018,10,13]],"date-time":"2018-10-13T00:00:00Z","timestamp":1539388800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2020,4]]},"DOI":"10.1007\/s00521-018-3795-4","type":"journal-article","created":{"date-parts":[[2018,10,13]],"date-time":"2018-10-13T12:40:59Z","timestamp":1539434459000},"page":"4025-4043","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["A TOPSIS multi-criteria decision method-based intelligent recurrent wavelet CMAC control system design for MIMO uncertain nonlinear systems"],"prefix":"10.1007","volume":"32","author":[{"given":"Tuan-Tu","family":"Huynh","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tien-Loc","family":"Le","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4575-5952","authenticated-orcid":false,"given":"Chih-Min","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,10,13]]},"reference":[{"issue":"4","key":"3795_CR1","doi-asserted-by":"crossref","first-page":"913","DOI":"10.1007\/s00521-016-2506-2","volume":"29","author":"JW Perng","year":"2018","unstructured":"Perng JW, Hsieh SC, Ma LS, Chen GY (2018) Design of robust PI control systems based on sensitivity analysis and genetic algorithms. Neural Comput Appl 29(4):913\u2013923","journal-title":"Neural Comput Appl"},{"key":"3795_CR2","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-319-11173-5","volume-title":"Advances and applications in sliding mode control systems","author":"AT Azar","year":"2015","unstructured":"Azar AT, Zhu Q (2015) Advances and applications in sliding mode control systems. Springer, New York"},{"issue":"6","key":"3795_CR3","doi-asserted-by":"crossref","first-page":"1839","DOI":"10.1007\/s40815-018-0482-7","volume":"20","author":"CM Lin","year":"2018","unstructured":"Lin CM, Huynh TT (2018) Function-link fuzzy cerebellar model articulation controller design for nonlinear chaotic systems using TOPSIS multiple attribute decision-making method. Int J Fuzzy Syst 20(6):1839\u20131856","journal-title":"Int J Fuzzy Syst"},{"key":"3795_CR4","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1016\/j.automatica.2015.11.007","volume":"64","author":"H Li","year":"2016","unstructured":"Li H, Shi P, Yao D, Wu L (2016) Observer-based adaptive sliding mode control for nonlinear Markovian jump systems. Automatica 64:133\u2013142","journal-title":"Automatica"},{"key":"3795_CR5","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-018-3413-5","author":"CF Hsu","year":"2018","unstructured":"Hsu CF, Kao WF (2018) Perturbation wavelet neural sliding mode position control for a voice coil motor driver. Neural Comput Appl. \nhttps:\/\/doi.org\/10.1007\/s00521-018-3413-5","journal-title":"Neural Comput Appl"},{"issue":"8","key":"3795_CR6","doi-asserted-by":"crossref","first-page":"2311","DOI":"10.1109\/TSMC.2017.2657557","volume":"47","author":"SF Su","year":"2017","unstructured":"Su SF, Chen MC, Hsueh YC (2017) A novel fuzzy modeling structure-decomposed fuzzy system. IEEE Trans Syst Man Cybern 47(8):2311\u20132317","journal-title":"IEEE Trans Syst Man Cybern"},{"issue":"12","key":"3795_CR7","doi-asserted-by":"crossref","first-page":"1495","DOI":"10.1007\/s00521-016-2666-0","volume":"29","author":"KTT Bui","year":"2018","unstructured":"Bui KTT, Tien Bui D, Zou J, Van Doan C, Revhaug I (2018) A novel hybrid artificial intelligent approach based on neural fuzzy inference model and particle swarm optimization for horizontal displacement modeling of hydropower dam. Neural Comput Appl 29(12):1495\u20131506","journal-title":"Neural Comput Appl"},{"key":"3795_CR8","doi-asserted-by":"crossref","first-page":"538","DOI":"10.1016\/j.apenergy.2017.11.072","volume":"211","author":"R Xiong","year":"2018","unstructured":"Xiong R, Cao J, Yu Q (2018) Reinforcement learning-based real-time power management for hybrid energy storage system in the plug-in hybrid electric vehicle. Appl Energy 211:538\u2013548","journal-title":"Appl Energy"},{"key":"3795_CR9","doi-asserted-by":"crossref","unstructured":"Bleuler S, Laumanns M, Thiele L, Zitzler E (2003) PISA\u2014a platform and programming language independent interface for search algorithms. In: Evolutionary multi-criterion optimization, pp 494\u2013508","DOI":"10.1007\/3-540-36970-8_35"},{"issue":"1","key":"3795_CR10","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1007\/s13042-014-0324-3","volume":"8","author":"S Mallick","year":"2017","unstructured":"Mallick S, Kar R, Mandal D, Ghoshal S (2017) Optimal sizing of CMOS analog circuits using gravitational search algorithm with particle swarm optimization. Int J Mach Learn Cybernet 8(1):309\u2013331","journal-title":"Int J Mach Learn Cybernet"},{"key":"3795_CR11","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-018-3579-x","author":"H Zhang","year":"2018","unstructured":"Zhang H, Ji Y, Huang W, Liu L (2018) Sitcom-star-based clothing retrieval for video advertising: a deep learning framework. Neural Comput Appl. \nhttps:\/\/doi.org\/10.1007\/s00521-018-3579-x","journal-title":"Neural Comput Appl"},{"key":"3795_CR12","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1007\/978-3-319-00065-7_28","volume":"88","author":"C Matuszek","year":"2013","unstructured":"Matuszek C, Herbst E, Zettlemoyer L, Fox D (2013) Learning to parse natural language commands to a robot control system. Experimental Robotics 88:403\u2013415","journal-title":"Experimental Robotics"},{"issue":"2","key":"3795_CR13","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1007\/s40313-016-0295-6","volume":"28","author":"TH Medeiros De","year":"2017","unstructured":"De Medeiros TH, Rocha HP, Torres FS, Takahashi RHC, Braga AP (2017) Multi-objective decision in machine learning. J Control Autom Electr Syst 28(2):217\u2013227","journal-title":"J Control Autom Electr Syst"},{"key":"3795_CR14","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.ab.2018.06.011","volume":"555","author":"NQK Le","year":"2018","unstructured":"Le NQK, Ho QT, Ou YY (2018) Classifying the molecular functions of Rab GTPases in membrane trafficking using deep convolutional neural networks. Anal Biochem 555:33\u201341","journal-title":"Anal Biochem"},{"key":"3795_CR15","volume-title":"Petri net synthesis for discrete event control of manufacturing systems","author":"M Zhou","year":"2012","unstructured":"Zhou M, DiCesare F (2012) Petri net synthesis for discrete event control of manufacturing systems. Springer, New York"},{"key":"3795_CR16","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.cmpb.2017.03.016","volume":"144","author":"JH Zhang","year":"2017","unstructured":"Zhang JH, Xia JJ, Garibaldi JM, Groumpos PP, Wang RB (2017) Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets. Comput Methods Progr Biomed 144:147\u2013163","journal-title":"Comput Methods Progr Biomed"},{"key":"3795_CR17","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2018.2837643","author":"RJ Rodr\u00edguez","year":"2018","unstructured":"Rodr\u00edguez RJ, Bernardi S, Zimmermann A (2018) An evaluation framework for comparative analysis of generalized stochastic petri net simulation techniques. IEEE Trans Syst Man Cybern. \nhttps:\/\/doi.org\/10.1109\/TSMC.2018.2837643","journal-title":"IEEE Trans Syst Man Cybern"},{"issue":"4","key":"3795_CR18","doi-asserted-by":"crossref","first-page":"1001","DOI":"10.1007\/s00521-016-2503-5","volume":"29","author":"S Hassan","year":"2018","unstructured":"Hassan S, Khanesar MA, Jaafar J, Khosravi A (2018) Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm. Neural Comput Appl 29(4):1001\u20131014","journal-title":"Neural Comput Appl"},{"key":"3795_CR19","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-018-3520-3","author":"VT Yen","year":"2018","unstructured":"Yen VT, Nan WY, Van Cuong P (2018) Recurrent fuzzy wavelet neural networks based on robust adaptive sliding mode control for industrial robot manipulators. Neural Comput Appl. \nhttps:\/\/doi.org\/10.1007\/s00521-018-3520-3","journal-title":"Neural Comput Appl"},{"issue":"3","key":"3795_CR20","doi-asserted-by":"crossref","first-page":"1613","DOI":"10.1109\/TFUZZ.2017.2737405","volume":"26","author":"N Wang","year":"2018","unstructured":"Wang N, Su SF, Yin J, Zheng Z, Er MJ (2018) Global asymptotic model-free trajectory-independent tracking control of an uncertain marine vehicle: an adaptive universe-based fuzzy control approach. IEEE Trans Fuzzy Syst 26(3):1613\u20131625","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"16","key":"3795_CR21","doi-asserted-by":"crossref","first-page":"2873","DOI":"10.1016\/j.neucom.2010.08.008","volume":"73","author":"D Lin","year":"2010","unstructured":"Lin D, Wang X, Nian F, Zhang Y (2010) Dynamic fuzzy neural networks modeling and adaptive backstepping tracking control of uncertain chaotic systems. Neurocomputing 73(16):2873\u20132881","journal-title":"Neurocomputing"},{"issue":"2","key":"3795_CR22","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1007\/s10291-016-0543-z","volume":"21","author":"Y Wang","year":"2017","unstructured":"Wang Y, Lu Z, Qu Y, Li L, Wang N (2017) Improving prediction performance of GPS satellite clock bias based on wavelet neural network. GPS Solut 21(2):523\u2013534","journal-title":"GPS Solut"},{"key":"3795_CR23","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.neunet.2017.09.005","volume":"97","author":"D Wang","year":"2018","unstructured":"Wang D, Liu D, Zhang Y, Li H (2018) Neural network robust tracking control with adaptive critic framework for uncertain nonlinear systems. Neural Netw 97:11\u201318","journal-title":"Neural Netw"},{"issue":"5","key":"3795_CR24","doi-asserted-by":"crossref","first-page":"1362","DOI":"10.1007\/s40815-017-0301-6","volume":"19","author":"CM Lin","year":"2017","unstructured":"Lin CM, Le TL (2017) PSO-self-organizing interval type-2 fuzzy neural network for antilock braking systems. Int J Fuzzy Syst 19(5):1362\u20131374","journal-title":"Int J Fuzzy Syst"},{"key":"3795_CR25","doi-asserted-by":"crossref","first-page":"576","DOI":"10.1016\/j.asoc.2017.01.052","volume":"55","author":"MR Akbarzadeh-T","year":"2017","unstructured":"Akbarzadeh-T MR, Hosseini S, Naghibi-Sistani MB (2017) Stable indirect adaptive interval type-2 fuzzy sliding-based control and synchronization of two different chaotic systems. Appl Soft Comput 55:576\u2013587","journal-title":"Appl Soft Comput"},{"issue":"5","key":"3795_CR26","doi-asserted-by":"crossref","first-page":"1344","DOI":"10.1007\/s40815-017-0342-x","volume":"19","author":"FJ Lin","year":"2017","unstructured":"Lin FJ, Chen SG, Sun IF (2017) Intelligent sliding-mode position control using recurrent wavelet fuzzy neural network for electrical power steering system. Int J Fuzzy Syst 19(5):1344\u20131361","journal-title":"Int J Fuzzy Syst"},{"issue":"3","key":"3795_CR27","doi-asserted-by":"crossref","first-page":"942","DOI":"10.1007\/s40815-016-0216-7","volume":"19","author":"CF Hsu","year":"2017","unstructured":"Hsu CF, Lee TT (2017) Emotional fuzzy sliding-mode control for unknown nonlinear systems. Int J Fuzzy Syst 19(3):942\u2013953","journal-title":"Int J Fuzzy Syst"},{"issue":"2","key":"3795_CR28","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1007\/s40815-017-0326-x","volume":"20","author":"Q Zhou","year":"2018","unstructured":"Zhou Q, Chao F, Lin CM (2018) A functional-link-based fuzzy brain emotional learning network for breast tumor classification and chaotic system synchronization. Int J Fuzzy Syst 20(2):349\u2013365","journal-title":"Int J Fuzzy Syst"},{"issue":"31","key":"3795_CR29","doi-asserted-by":"crossref","first-page":"2239","DOI":"10.1016\/j.neucom.2017.11.009","volume":"275","author":"CM Lin","year":"2018","unstructured":"Lin CM, Le TL, Huynh TT (2018) Self-evolving function-link interval type-2 fuzzy neural network for nonlinear system identification and control. Neurocomputing 275(31):2239\u20132250","journal-title":"Neurocomputing"},{"key":"3795_CR30","volume-title":"Multiple attribute decision making: methods and applications: a state-of-the-art survey","author":"CL Hwang","year":"1981","unstructured":"Hwang CL, Yoon K (1981) Multiple attribute decision making: methods and applications: a state-of-the-art survey. Springer, New York"},{"key":"3795_CR31","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.energy.2017.11.160","volume":"144","author":"N Mao","year":"2018","unstructured":"Mao N, Song M, Pan D, Deng S (2018) Comparative studies on using RSM and TOPSIS methods to optimize residential air conditioning systems. Energy 144:98\u2013109","journal-title":"Energy"},{"key":"3795_CR32","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.techfore.2017.05.034","volume":"131","author":"J Ouenniche","year":"2018","unstructured":"Ouenniche J, P\u00e9rez-Gladish B, Bouslah K (2018) An out-of-sample framework for TOPSIS-based classifiers with application in bankruptcy prediction. Technol Forecast Soc Change 131:111\u2013116","journal-title":"Technol Forecast Soc Change"},{"issue":"1","key":"3795_CR33","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1007\/s12351-015-0221-x","volume":"17","author":"L Liu","year":"2017","unstructured":"Liu L, Liu X, Pei J, Fan W, Pardalos PM (2017) A study on decision making of cutting stock with frustum of cone bars. Oper Res Int J 17(1):187\u2013204","journal-title":"Oper Res Int J"},{"key":"3795_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2018.07.011","author":"R Kaur","year":"2018","unstructured":"Kaur R, Singh S, Kumar H (2018) AuthCom: Authorship verification and compromised account detection in online social networks using AHP-TOPSIS embedded profiling based technique. Expert Syst Appl. \nhttps:\/\/doi.org\/10.1016\/j.eswa.2018.07.011","journal-title":"Expert Syst Appl"},{"issue":"5","key":"3795_CR35","first-page":"292","volume":"9","author":"A Mayyas","year":"2016","unstructured":"Mayyas A, Omar MA, Hayajneh MT (2016) Eco-material selection using fuzzy TOPSIS method. Int J Sustain Eng 9(5):292\u2013304","journal-title":"Int J Sustain Eng"},{"issue":"6","key":"3795_CR36","doi-asserted-by":"crossref","first-page":"1419","DOI":"10.1007\/s13762-016-0982-7","volume":"13","author":"A Afsordegan","year":"2016","unstructured":"Afsordegan A, S\u00e1nchez M, Agell N, Zahedi S, Cremades LV (2016) Decision making under uncertainty using a qualitative TOPSIS method for selecting sustainable energy alternatives. Int J Environ Sci Technol 13(6):1419\u20131432","journal-title":"Int J Environ Sci Technol"},{"key":"3795_CR37","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4471-4375-8","volume-title":"Decision making in manufacturing environment using graph theory and fuzzy multiple attribute decision making methods","author":"RV Rao","year":"2013","unstructured":"Rao RV (2013) Decision making in manufacturing environment using graph theory and fuzzy multiple attribute decision making methods, vol 2. Springer, New York"},{"issue":"3","key":"3795_CR38","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1115\/1.3426922","volume":"97","author":"JS Albus","year":"1975","unstructured":"Albus JS (1975) A new approach to manipulator control: the cerebellar model articulation controller (CMAC). J Dyn Syst Meas Control 97(3):220\u2013227","journal-title":"J Dyn Syst Meas Control"},{"issue":"9","key":"3795_CR39","doi-asserted-by":"crossref","first-page":"11836","DOI":"10.1016\/j.eswa.2009.04.020","volume":"36","author":"CF Hsu","year":"2009","unstructured":"Hsu CF, Chung CM, Lin CM, Hsu CY (2009) Adaptive CMAC neural control of chaotic systems with a PI-type learning algorithm. Expert Syst Appl 36(9):11836\u201311843","journal-title":"Expert Syst Appl"},{"issue":"2","key":"3795_CR40","doi-asserted-by":"crossref","first-page":"981","DOI":"10.1016\/j.chaos.2009.02.028","volume":"42","author":"CM Lin","year":"2009","unstructured":"Lin CM, Peng YF, Lin MH (2009) CMAC-based adaptive backstepping synchronization of uncertain chaotic systems. Chaos Solitons Fractals 42(2):981\u2013988","journal-title":"Chaos Solitons Fractals"},{"issue":"9","key":"3795_CR41","doi-asserted-by":"crossref","first-page":"1377","DOI":"10.1109\/TNN.2009.2013852","volume":"20","author":"CM Lin","year":"2009","unstructured":"Lin CM, Chen TY (2009) Self-organizing CMAC control for a class of MIMO uncertain nonlinear systems. IEEE Trans Neural Netw 20(9):1377\u20131384","journal-title":"IEEE Trans Neural Netw"},{"issue":"5","key":"3795_CR42","doi-asserted-by":"crossref","first-page":"1814","DOI":"10.1109\/TIE.2009.2032203","volume":"57","author":"CH Chiu","year":"2010","unstructured":"Chiu CH (2010) The design and implementation of a wheeled inverted pendulum using an adaptive output recurrent cerebellar model articulation controller. IEEE Trans Ind Electron 57(5):1814\u20131822","journal-title":"IEEE Trans Ind Electron"},{"issue":"2","key":"3795_CR43","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1109\/TCST.2014.2325897","volume":"23","author":"CM Lin","year":"2015","unstructured":"Lin CM, Li HY (2015) Dynamic petri fuzzy cerebellar model articulation controller design for a magnetic levitation system and a two-axis linear piezoelectric ceramic motor drive system. IEEE Trans Control Syst Technol 23(2):693\u2013699","journal-title":"IEEE Trans Control Syst Technol"},{"issue":"16","key":"3795_CR44","doi-asserted-by":"crossref","first-page":"4593","DOI":"10.1007\/s00500-016-2204-0","volume":"21","author":"C Macnab","year":"2017","unstructured":"Macnab C (2017) Creating a CMAC with overlapping basis functions in order to prevent weight drift. Soft Comput 21(16):4593\u20134600","journal-title":"Soft Comput"},{"key":"3795_CR45","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-017-3182-6","author":"C Macnab","year":"2017","unstructured":"Macnab C (2017) Modifying CMAC adaptive control with weight smoothing in order to avoid overlearning and bursting. Neural Comput Appl. \nhttps:\/\/doi.org\/10.1007\/s00521-017-3182-6","journal-title":"Neural Comput Appl"},{"issue":"1","key":"3795_CR46","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1145\/584091.584093","volume":"5","author":"CE Shannon","year":"2001","unstructured":"Shannon CE (2001) A mathematical theory of communication. Mobile Comput Commun Rev 5(1):3\u201355","journal-title":"Mobile Comput Commun Rev"},{"key":"3795_CR47","volume-title":"Multiple criteria decision making","author":"M Zeleny","year":"1982","unstructured":"Zeleny M (1982) Multiple criteria decision making. McGraw-Hill, New York"},{"issue":"1","key":"3795_CR48","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1109\/91.481843","volume":"4","author":"BS Chen","year":"1996","unstructured":"Chen BS, Lee CH, Chang YC (1996) Tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach. IEEE Trans Fuzzy Syst 4(1):32\u201343","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"6","key":"3795_CR49","doi-asserted-by":"crossref","first-page":"1147","DOI":"10.1109\/TFUZZ.2012.2191789","volume":"20","author":"CM Lin","year":"2012","unstructured":"Lin CM, Li HY (2012) TSK fuzzy CMAC-based robust adaptive backstepping control for uncertain nonlinear systems. IEEE Trans Fuzzy Syst 20(6):1147\u20131154","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"2","key":"3795_CR50","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1007\/s00521-012-1242-5","volume":"24","author":"CM Lin","year":"2014","unstructured":"Lin CM, Tai CF, Chung CC (2014) Intelligent control system design for UAV using a recurrent wavelet neural network. Neural Comput Appl 24(2):487\u2013496","journal-title":"Neural Comput Appl"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-018-3795-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-018-3795-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-018-3795-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,4,6]],"date-time":"2020-04-06T08:17:10Z","timestamp":1586161030000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-018-3795-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,10,13]]},"references-count":50,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2020,4]]}},"alternative-id":["3795"],"URL":"https:\/\/doi.org\/10.1007\/s00521-018-3795-4","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,10,13]]},"assertion":[{"value":"12 March 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 September 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 October 2018","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}