{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T22:54:25Z","timestamp":1781564065612,"version":"3.54.5"},"reference-count":68,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2020,7,7]],"date-time":"2020-07-07T00:00:00Z","timestamp":1594080000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,7,7]],"date-time":"2020-07-07T00:00:00Z","timestamp":1594080000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2020,11]]},"DOI":"10.1007\/s10489-020-01744-x","type":"journal-article","created":{"date-parts":[[2020,7,7]],"date-time":"2020-07-07T01:03:41Z","timestamp":1594083821000},"page":"3990-4016","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":98,"title":["Economic data analytic AI technique on IoT edge devices for health monitoring of agriculture machines"],"prefix":"10.1007","volume":"50","author":[{"given":"Neeraj","family":"Gupta","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mahdi","family":"Khosravy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nilesh","family":"Patel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nilanjan","family":"Dey","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saurabh","family":"Gupta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hemant","family":"Darbari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5541-6319","authenticated-orcid":false,"given":"Rub\u00e9n Gonz\u00e1lez","family":"Crespo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,7,7]]},"reference":[{"key":"1744_CR1","doi-asserted-by":"crossref","unstructured":"Vimal S, Khari M, Dey N, Crespo RG, Robinson YH (2020) Enhanced resource allocation in mobile edge computing using reinforcement learning based MOACO algorithm for IIOT, Computer Communications.","DOI":"10.1016\/j.comcom.2020.01.018"},{"issue":"6","key":"1744_CR2","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1109\/MWC.2015.7368833","volume":"22","author":"JA Guerrero-Ibanez","year":"2015","unstructured":"Guerrero-Ibanez JA, Zeadally S, Contreras-Castillo J (2015) Integration challenges of intelligent transportation systems with connected vehicle, cloud computing, and internet of things technologies. IEEE Wirel Commun 22(6):122\u2013128","journal-title":"IEEE Wirel Commun"},{"issue":"1","key":"1744_CR3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.compag.2005.09.003","volume":"50","author":"N Wang","year":"2006","unstructured":"Wang N, Zhang N, Wang M (2006) Wireless sensors in agriculture and food industry\u2014Recent development and future perspective. Comput Electron Agric 50(1):1\u201314","journal-title":"Comput Electron Agric"},{"key":"1744_CR4","unstructured":"Zhang Q, Reid JF, Noguchi N (1999) Agricultural vehicle navigation using multiple guidance sensors. In: Proceedings of the International Conference on Field and Service Robotics, pp 293\u2013298. August"},{"key":"1744_CR5","doi-asserted-by":"crossref","unstructured":"Dey N, Mahalle PN, Shafi PM, Kimabahune VV, Hassanien AE (2020) Internet of things smart computing and technology: a roadmap ahead","DOI":"10.1007\/978-3-030-39047-1"},{"key":"1744_CR6","doi-asserted-by":"crossref","first-page":"100307","DOI":"10.1016\/j.njas.2019.100307","volume":"90","author":"JE Relf-Eckstein","year":"2019","unstructured":"Relf-Eckstein JE, Ballantyne AT, Phillips PWB (2019) Farming Reimagined: A case study of autonomous farm equipment and creating an innovation opportunity space for broadacre smart farming. NJAS-Wageningen J Life Sci 90:100307","journal-title":"NJAS-Wageningen J Life Sci"},{"key":"1744_CR7","doi-asserted-by":"crossref","unstructured":"Vimal S, Khari M, Dey N, Crespo RG, Robinson YH (2020) Enhanced resource allocation in mobile edge computing using reinforcement learning based MOACO algorithm for IIOT. Computer Communications.","DOI":"10.1016\/j.comcom.2020.01.018"},{"key":"1744_CR8","doi-asserted-by":"crossref","unstructured":"Khosravy M, Gupta N, Patel N, Dey N, Nitta N, Babaguchi N. (2020) Probabilistic stone\u2019s blind source separation with application to channel estimation and multi-node identification in MIMO IoT green communication and multimedia systems, Computer Communications","DOI":"10.1016\/j.comcom.2020.04.042"},{"key":"1744_CR9","doi-asserted-by":"crossref","unstructured":"Vimal S, Khari M, Crespo RG, Kalaivani L, Dey N, Kaliappan M (2020) Energy enhancement using Multiobjective Ant colony optimisation with Double Q learning algorithm for IoT based cognitive radio networks. Computer Communications","DOI":"10.1016\/j.comcom.2020.03.004"},{"issue":"3","key":"1744_CR10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4018\/IJACI.2017070101","volume":"8","author":"M Sarkar","year":"2017","unstructured":"Sarkar M, Banerjee S, Badr Y, Sangaiah AK (2017) Configuring a trusted cloud service model for smart city exploration using hybrid intelligence. Int J Amb Comput Intell (IJACI) 8(3):1\u201321","journal-title":"Int J Amb Comput Intell (IJACI)"},{"key":"1744_CR11","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.jnca.2016.01.010","volume":"67","author":"M D\u00edaz","year":"2016","unstructured":"D\u00edaz M, Mart\u00edn C, Rubio B (2016) State-of-the-art, challenges, and open issues in the integration of Internet of things and cloud computing. J Netw Comput Appl 67:99\u2013117","journal-title":"J Netw Comput Appl"},{"issue":"3","key":"1744_CR12","doi-asserted-by":"crossref","first-page":"1628","DOI":"10.1109\/COMST.2017.2682318","volume":"19","author":"P Mach","year":"2017","unstructured":"Mach P, Becvar Z (2017) Mobile edge computing: A survey on architecture and computation offloading. IEEE Commun Surv 19(3):1628\u20131656","journal-title":"IEEE Commun Surv"},{"key":"1744_CR13","doi-asserted-by":"crossref","unstructured":"Aram S, Troiano A, Pasero E (2012) Environment sensing using smartphone. In: 2012 IEEE Sensors applications symposium proceedings, pp 1\u20134. IEEE","DOI":"10.1109\/SAS.2012.6166275"},{"issue":"4","key":"1744_CR14","doi-asserted-by":"crossref","first-page":"2718","DOI":"10.3906\/elk-1807-165","volume":"27","author":"S Gupta","year":"2019","unstructured":"Gupta S, Khosravy M, Gupta N, Darbari H (2019) In-field failure assessment of tractor hydraulic system operation via pseudospectrum of acoustic measurements. Turk J Electr Eng CO 27(4):2718\u20132729","journal-title":"Turk J Electr Eng CO"},{"key":"1744_CR15","unstructured":"Gupta S, Gupta N, Tiwari BN, Khosravy M, Senzio-Savino B, Asharif F, Asharif MR (2016) Tractor oil pump fault diagnosis by pseudo-spectrum analysis of vehicle sound records. In: Proceedings of the 31st international technical conference on circuits\/systems. Computers and communications"},{"key":"1744_CR16","doi-asserted-by":"crossref","unstructured":"Bohlin M, Forsgren M, Hoist A, Levin B, Aronsson M, Steinert R (2008) Reducing vehicle maintenance using condition monitoring and dynamic planning","DOI":"10.1049\/ic:20080329"},{"key":"1744_CR17","doi-asserted-by":"crossref","unstructured":"Gillblad D, Steinert R, Holst A (2008) Fault-tolerant incremental diagnosis with limited historical data. In: 2008 International conference on prognostics and health management. IEEE, pp 1\u20138","DOI":"10.1109\/PHM.2008.4711451"},{"issue":"4","key":"1744_CR18","doi-asserted-by":"crossref","first-page":"25","DOI":"10.4018\/IJACI.2019100102","volume":"10","author":"B Wu","year":"2019","unstructured":"Wu B, Wang H (2019) A lane identifying approach of the intelligent vehicle in complex condition: intelligent vehicle in complex condition. Int J Amb Comput Intell(IJACI) 10(4):25\u2013 44","journal-title":"Int J Amb Comput Intell(IJACI)"},{"issue":"3","key":"1744_CR19","doi-asserted-by":"crossref","first-page":"22","DOI":"10.4018\/IJACI.2017070102","volume":"8","author":"AH Ali","year":"2017","unstructured":"Ali AH, Atia A, Mostafa MSM (2017) Recognizing driving behavior and road anomaly using smartphone sensors. Int J Amb Comput Intell (IJACI) 8(3):22\u201337","journal-title":"Int J Amb Comput Intell (IJACI)"},{"key":"1744_CR20","doi-asserted-by":"crossref","unstructured":"V\u00f6lgyesi P, Szilv\u00e1si S, J\u00e1nos S, L\u00e9deczi \u00c1 (2011) External smart microphone for mobile phones. In: 2011 Fifth international conference on sensing technology. IEEE, pp 171\u2013176","DOI":"10.1109\/ICSensT.2011.6136957"},{"issue":"2","key":"1744_CR21","first-page":"216","volume":"98","author":"M Sarwar","year":"2013","unstructured":"Sarwar M, Soomro TR (2013) Impact of smartphone\u2019s on society. Eur J Sci Res 98(2):216\u2013226","journal-title":"Eur J Sci Res"},{"issue":"1","key":"1744_CR22","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1186\/s13174-018-0087-2","volume":"9","author":"R Boutaba","year":"2018","unstructured":"Boutaba R, Salahuddin MA, Limam N, Sara S, Shahriar N, Estrada-Solano F, Caicedo OM (2018) A comprehensive survey on machine learning for networking: evolution, applications and research opportunities. J Internet Serv Appl 9(1):16","journal-title":"J Internet Serv Appl"},{"issue":"12","key":"1744_CR23","doi-asserted-by":"crossref","first-page":"4474","DOI":"10.3390\/s18124474","volume":"18","author":"AC Djedouboum","year":"2018","unstructured":"Djedouboum AC, Ari A, Adamou A, Gueroui AM, Mohamadou A, Aliouat Z (2018) Big data collection in large-scale wireless sensor networks. Sensors 18(12):4474","journal-title":"Sensors"},{"key":"1744_CR24","doi-asserted-by":"crossref","unstructured":"Burnett K, Samavi S, Waslanderm S, Barfoot T, Schoellig A (2019) aUToTrack: a lightweight object detection and tracking system for the sae autodrive challenge. In: 2019 16th conference on Computer and Robot Vision (CRV). IEEE, pp 209\u2013216","DOI":"10.1109\/CRV.2019.00036"},{"key":"1744_CR25","unstructured":"https:\/\/www.precisionfarmingdealer.com\/keywords\/AutoTrac"},{"key":"1744_CR26","unstructured":"https:\/\/www.deere.com\/en\/our-company\/news-and-announcements\/news-releases\/2017\/agriculture\/2017jun1_4640_universal_display.html"},{"key":"1744_CR27","doi-asserted-by":"crossref","unstructured":"Ganguly K, Gulati A, von Braun J (2017). Innovations spearheading the next transformations in India\u2019s agriculture","DOI":"10.2139\/ssrn.3000345"},{"key":"1744_CR28","unstructured":"Lohento K, Sotannde M (2019) Business models and key success drivers of agtech start-ups CTA"},{"issue":"3","key":"1744_CR29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2971482","volume":"49","author":"R Coppola","year":"2016","unstructured":"Coppola R, Morisio M (2016) Connected car: technologies, issues, future trends. ACM Comput Surv (CSUR) 49(3):1\u201336","journal-title":"ACM Comput Surv (CSUR)"},{"key":"1744_CR30","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.inffus.2017.10.006","volume":"42","author":"Q Zhang","year":"2018","unstructured":"Zhang Q, Yang LT, Chen Z, Li P (2018) A survey on deep learning for big data. Information Fusion 42:146\u2013157","journal-title":"Information Fusion"},{"key":"1744_CR31","doi-asserted-by":"crossref","unstructured":"Pasupa K, Sunhem W (2016) A comparison between shallow and deep architecture classifiers on small dataset. In: 2016 8Th international conference on information technology and electrical engineering (ICITEE). IEEE, pp 1\u20136","DOI":"10.1109\/ICITEED.2016.7863293"},{"key":"1744_CR32","doi-asserted-by":"crossref","unstructured":"Smiti P, Srivastava S, Rakesh N (2018) Video and audio streaming issues in multimedia application. In: 2018 8Th international conference on cloud computing, data science & engineering (confluence). IEEE, pp 360\u2013365","DOI":"10.1109\/CONFLUENCE.2018.8442823"},{"key":"1744_CR33","doi-asserted-by":"crossref","unstructured":"Leme BCC, Almeida LF, Bizarria JWP, Bizarria FCP, Soares AMS, Ramos MAC (2017) Development of a low-cost tool for semi-automatic classification and counting of particles in industrial oils. In: IEEE international conference on Industrial Engineering and Engineering Management (IEEM), p 2017","DOI":"10.1109\/IEEM.2017.8290227"},{"key":"1744_CR34","doi-asserted-by":"crossref","unstructured":"Renius KT (2020) Tractor and implement. In: Fundamentals of tractor design. Springer, Cham, pp 217\u2013260","DOI":"10.1007\/978-3-030-32804-7_7"},{"key":"1744_CR35","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1007\/s11760-010-0161-0","volume":"5","author":"M Khosravy","year":"2011","unstructured":"Khosravy M, Asharif MR, Yamashita K (2011) A theoretical discussion onthe foundation of stone\u2019s blind source separation. Signal Image Video Process 5:379\u2013388","journal-title":"Signal Image Video Process"},{"key":"1744_CR36","unstructured":"Khosravy M, Alsharif MR, Yamashita K (2008) A probabilistic short-length linear predictability approach to blind source separation. In: ITC-CSCC:International Technical Conference on Circuits Systems, Computers and Communications, pp 381\u2013 384"},{"key":"1744_CR37","doi-asserted-by":"crossref","unstructured":"Khosravy M, Alsharif MR, Yamashita K (2009) A pdf-matched modification to stone\u2019s measure of predictability for blind source separation. In: International symposium on neural networks. Springer, pp 219\u2013228","DOI":"10.1007\/978-3-642-01507-6_26"},{"key":"1744_CR38","unstructured":"Khosravy M (2010) Blind source separation and its application to speech, image and MIMO-OFDM communication systems, Ph.D. thesis University ofthe Ryukyus"},{"key":"1744_CR39","unstructured":"Lartillot O, Toiviainen P (2007) A Matlab toolbox for musical feature extraction from audio. In: International conference on digital audio effects, pp 237\u2013244"},{"key":"1744_CR40","volume-title":"Introduction to audio analysis: a MATLAB\u00ae approach","author":"T Giannakopoulos","year":"2014","unstructured":"Giannakopoulos T, Pikrakis A (2014) Introduction to audio analysis: a MATLAB\u00ae approach. Academic, New York"},{"issue":"6","key":"1744_CR41","doi-asserted-by":"crossref","first-page":"3757","DOI":"10.1109\/TIE.2015.2417501","volume":"62","author":"Z Gao","year":"2015","unstructured":"Gao Z, Cecati C, Ding SX (2015) A survey of fault diagnosis and fault-tolerant techniques\u2014Part i: Fault diagnosis with model-based and signal-based approaches. IEEE Trans Ind Electron 62(6):3757\u20133767","journal-title":"IEEE Trans Ind Electron"},{"key":"1744_CR42","doi-asserted-by":"crossref","unstructured":"Sen PC, Hajra M, Ghosh M (2020) Supervised classification algorithms in machine learning: a survey and review. Springer, Singapore, pp 9\u2013111","DOI":"10.1007\/978-981-13-7403-6_11"},{"issue":"1","key":"1744_CR43","first-page":"3893","volume":"15","author":"M Saouabi","year":"2020","unstructured":"Saouabi M, Ezzati A (2020) Data mining classification algorithms. Comput Sci 15(1):3893\u201394","journal-title":"Comput Sci"},{"key":"1744_CR44","doi-asserted-by":"crossref","first-page":"48455","DOI":"10.1109\/ACCESS.2018.2867954","volume":"6","author":"N Gupta","year":"2018","unstructured":"Gupta N, Khosravy M, Patel N, Senjyu T (2018) A bi-level evolutionary optimization for coordinated transmission expansion planning. IEEE Access 6:48455\u201348477","journal-title":"IEEE Access"},{"key":"1744_CR45","doi-asserted-by":"crossref","unstructured":"Singh G, Gupta N, Khosravy M (2015) New crossover operators for real coded genetic algorithm (RCGA). In: 2015 International conference on intelligent informatics and biomedical sciences (ICIIBMS). IEEE, pp 135\u2013140","DOI":"10.1109\/ICIIBMS.2015.7439507"},{"key":"1744_CR46","doi-asserted-by":"crossref","DOI":"10.1007\/978-981-15-2133-1","volume-title":"Frontier applications of nature inspired computation","author":"M Khosravy","year":"2020","unstructured":"Khosravy M, Gupta N, Patel N, Senjyu T (2020) Frontier applications of nature inspired computation. Springer, Cham"},{"key":"1744_CR47","doi-asserted-by":"crossref","unstructured":"Gupta N, Khosravy M, Patel N, Dey N (2020) Mahela, O.P, Mendelian evolutionary theory optimization algorithm","DOI":"10.36227\/techrxiv.12095802.v1"},{"key":"1744_CR48","doi-asserted-by":"crossref","unstructured":"Gupta N, Khosravy M, Mahela OP, Patel N (2020) Plant biology inspired genetic algorithm: Superior efficiency to firefly optimizer. In: Applications of firefly algorithm and its variants. Springer, pp 193\u2013219","DOI":"10.1007\/978-981-15-0306-1_9"},{"key":"1744_CR49","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.procs.2018.07.218","volume":"126","author":"N Gupta","year":"2018","unstructured":"Gupta N, Khosravy M, Patel N, Sethi I (2018) Evolutionary optimization based on biological evolution in plants. Procedia Comput Sci 126:146\u2013155","journal-title":"Procedia Comput Sci"},{"key":"1744_CR50","doi-asserted-by":"crossref","unstructured":"Gupta N, Khosravy M, Patel N, Gupta S, Varshney G (2020) Artificial neural network trained by plant genetics-inspired optimizer. In: Frontier applications of nature inspired computation, Springer","DOI":"10.1007\/978-981-15-2133-1"},{"key":"1744_CR51","doi-asserted-by":"crossref","unstructured":"Khosravy M, Gupta N, Patel N, Mahela OP, Varshney G (2020) Tracing the points in search space in plant biology genetics algorithm optimization. In: Frontier applications of nature inspired computation. Springer, Singapore, pp 180\u2013195","DOI":"10.1007\/978-981-15-2133-1_8"},{"key":"1744_CR52","doi-asserted-by":"crossref","unstructured":"Gupta N, Khosravy M, Patel N, Mahela OP, Varshney G (2020) Plant Genetics-Inspired evolutionary optimization: a descriptive tutorial. In: Frontier applications of nature inspired computation. Springer, Singapore, pp 53\u201377","DOI":"10.1007\/978-981-15-2133-1_3"},{"key":"1744_CR53","doi-asserted-by":"crossref","unstructured":"Gupta N, Khosravy M, Patel N, Gupta S, Varshney G (2020) Evolutionary artificial neural networks: Comparative study on state of the art optimizers. In: Frontier applications of nature inspired computation, Springer","DOI":"10.1007\/978-981-15-2133-1_14"},{"issue":"4","key":"1744_CR54","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1109\/TASSP.1980.1163420","volume":"28","author":"S Davis","year":"1980","unstructured":"Davis S, Mermelstein P (1980) Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences. IEEE Trans Acoust Speech Signal Process 28(4):357\u2013366","journal-title":"IEEE Trans Acoust Speech Signal Process"},{"key":"1744_CR55","unstructured":"Schaffer J, Whitley D, Eshelman LJ (1992) David Combinations of genetic algorithms and neural networks: A survey of the state of the art. In: [Proceedings] COGANN-92: international workshop on combinations of genetic algorithms and neural networks. IEEE, pp 1\u201337"},{"key":"1744_CR56","doi-asserted-by":"crossref","unstructured":"Gupta N, Patel N, Tiwari BN, Khosravy M (2018) Genetic algorithm based on enhanced selection and log-scaled mutation technique. In: Proceedings of the Future Technologies Conference, Springer, Cham, pp. 730\u2013748, November","DOI":"10.1007\/978-3-030-02686-8_55"},{"issue":"4","key":"1744_CR57","doi-asserted-by":"crossref","first-page":"137","DOI":"10.22213\/2410-9304-2019-4-137-142","volume":"17","author":"VA Tenenev","year":"2020","unstructured":"Tenenev VA, Shaura AS (2020) Solving general nonlinear programming problems with a genetic algorithm. Intellekt Sist Proizv 17(4):137\u2013142","journal-title":"Intellekt Sist Proizv"},{"key":"1744_CR58","doi-asserted-by":"crossref","unstructured":"Yin C, Luo Z, Ni M, Cen K (1998) Predicting coal ash fusion temperature with a back-propagation neural network model, vol 77","DOI":"10.1016\/S0016-2361(98)00077-5"},{"issue":"04","key":"1744_CR59","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1142\/S0129065791000261","volume":"2","author":"EM Johansson","year":"1991","unstructured":"Johansson EM, Dowla FU, Goodman DM (1991) Backpropagation learning for multilayer feed-forward neural networks using the conjugate gradient method. Int J Neural Sys 2(04):291\u2013301","journal-title":"Int J Neural Sys"},{"key":"1744_CR60","doi-asserted-by":"crossref","unstructured":"Kalathingal MSH, Basak S, Mitra J (2020). Artificial neural network modeling and genetic algorithm optimization of process parameters in fluidized bed drying of green tea leaves. J Food Process Eng e13128","DOI":"10.1111\/jfpe.13128"},{"key":"1744_CR61","doi-asserted-by":"crossref","unstructured":"Samanta B, Al-Balushi KR, Al-Araimi SA (2001) Use of genetic algorithm and artificial neural network for gear condition diagnostics, Elsevier Science Ltd","DOI":"10.1016\/B978-008044036-1\/50052-4"},{"key":"1744_CR62","volume-title":"Neural network design","author":"MT Also Hagan","year":"1996","unstructured":"Also Hagan MT, Demuth HB, Beale MH (1996) Neural network design. PWS Publishing, Boston"},{"issue":"4","key":"1744_CR63","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1016\/S0893-6080(05)80056-5","volume":"6","author":"Author links open overlay panelMartin FodsletteMoller","year":"1993","unstructured":"Author links open overlay panelMartin FodsletteMoller (1993) A scaled conjugate gradient algorithm for fast supervised learning. Neural Netw 6(4):525\u2013533","journal-title":"Neural Netw"},{"key":"1744_CR64","doi-asserted-by":"crossref","unstructured":"Kaur H, Kaur M (2020) Fault classification in a transmission line using levenberg\u2013marquardt algorithm based artificial neural network, Springer, Singapore","DOI":"10.1007\/978-981-15-0132-6_9"},{"key":"1744_CR65","unstructured":"Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez J-C, M\u00fcller M, Siegert S (2018). pROC: display and analyze ROC curves. R Package Version 1"},{"key":"1744_CR66","doi-asserted-by":"crossref","unstructured":"Choi K, Fazekas G, Sandler M, Cho K (2018) A comparison of audio signal preprocessing methods for deep neural networks on music tagging. In: 2018 26th European Signal Processing Conference (EUSIPCO). IEEE, pp 1870\u20131874","DOI":"10.23919\/EUSIPCO.2018.8553106"},{"issue":"1","key":"1744_CR67","first-page":"1","volume":"6","author":"S Kumar","year":"2020","unstructured":"Kumar S, Solanki VK, Choudhary KC, Selamat A, Crespo RG (2020) Comparative study on Ant Colony Optimization (ACO) and K-means clustering approaches for jobs scheduling and energy optimization model in Internet of Things (IoT). IJIMAI 6(1):1\u201310","journal-title":"IJIMAI"},{"issue":"1","key":"1744_CR68","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1007\/s40032-019-00519-9","volume":"101","author":"P Agrawal","year":"2020","unstructured":"Agrawal P, Jayaswal P (2020) Diagnosis and classifications of bearing faults using artificial neural network and support vector machine. J Inst Eng (India) C 101(1):61\u201372","journal-title":"J Inst Eng (India) C"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-020-01744-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-020-01744-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-020-01744-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,7,7]],"date-time":"2021-07-07T00:07:19Z","timestamp":1625616439000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-020-01744-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,7]]},"references-count":68,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2020,11]]}},"alternative-id":["1744"],"URL":"https:\/\/doi.org\/10.1007\/s10489-020-01744-x","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,7,7]]},"assertion":[{"value":"7 July 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with Ethical Standards"}},{"value":"The authors declares that they have no known competing financial interests or personal relationship that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflict of interests"}}]}}