{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T01:22:22Z","timestamp":1783041742775,"version":"3.54.6"},"reference-count":38,"publisher":"IOP Publishing","issue":"4","license":[{"start":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T00:00:00Z","timestamp":1701302400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T00:00:00Z","timestamp":1701302400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["41874081"],"award-info":[{"award-number":["41874081"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"the Science and Technology Innovation Program of Hunan Province","award":["2023RC1014"],"award-info":[{"award-number":["2023RC1014"]}]},{"name":"the Open Research Fund Program of Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Central South University), Ministry of Education","award":["2023YSJS07"],"award-info":[{"award-number":["2023YSJS07"]}]},{"name":"Research Foundation of Education Bureau of Hunan Province, China","award":["22A0457"],"award-info":[{"award-number":["22A0457"]}]},{"DOI":"10.13039\/501100004735","name":"Natural Science Foundation of Hunan Province","doi-asserted-by":"crossref","award":["2023JJ40222"],"award-info":[{"award-number":["2023JJ40222"]}],"id":[{"id":"10.13039\/501100004735","id-type":"DOI","asserted-by":"crossref"}]},{"name":"the Excellent Young Scientist Foundation of Hunan Provincial Education Department","award":["22B0694"],"award-info":[{"award-number":["22B0694"]}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Mach. Learn.: Sci. Technol."],"published-print":{"date-parts":[[2023,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The application of the electromagnetic method has accelerated due to the demand for the development of mineral resource, however the strong electromagnetic interference seriously lowers the data quality, resolution and detect effect. To suppress the electromagnetic interference, this paper proposes an intelligent processing method based on detrended and identification, and applies for wide field electromagnetic method (WFEM) data. First, we combined the improved intrinsic time scale decomposition and detrended fluctuation analysis algorithm for removing the trend noise. Then, we extracted the time domain characteristics of the WFEM data after removing the trend noise. Next, the arithmetic optimization algorithm was utilized to search for the optimal smoothing factor of the probabilistic neural network (PNN) algorithm, which realized to intelligently identify the noise data and WFEM effective data. Finally, the Fourier transform was performed to extract the spectrum amplitude of the effective frequency points from the reconstructed WFEM data, and the electric field curve was obtained. In these studies and applications, the fuzzy c-mean and PNN algorithm are contrasted. The proposed method indicated that the trend noise can be adaptively extracted and eliminated, the abnormal waveform or noise interference can be intelligently identified, the reconstructed WFEM data can effectively recover the pseudo-random signal waveform, and the shape of electric field curves were more stable. Simulation experiments and measured applications has verified that the proposed method can provide technical support for deep underground exploration.<\/jats:p>","DOI":"10.1088\/2632-2153\/ad0c40","type":"journal-article","created":{"date-parts":[[2023,11,13]],"date-time":"2023-11-13T22:46:00Z","timestamp":1699915560000},"page":"045041","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Intelligent processing of electromagnetic data using detrended and identification"],"prefix":"10.1088","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9156-9742","authenticated-orcid":true,"given":"Xian","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8435-4655","authenticated-orcid":true,"given":"Diquan","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4680-5130","authenticated-orcid":true,"given":"Bei","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanfang","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yao","family":"Mo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2023,11,30]]},"reference":[{"key":"mlstad0c40bib1","first-page":"632","article-title":"On the closed addition in a three element set and the 2n sequence pseudo-random signal coding","volume":"41","author":"He","year":"2010","journal-title":"J. Cent. South Univ."},{"key":"mlstad0c40bib2","first-page":"1065","article-title":"Wide field electromagnetic sounding methods","volume":"41","author":"He","year":"2010","journal-title":"J. Cent. South Univ."},{"key":"mlstad0c40bib3","first-page":"1666","article-title":"Mathematical analysis and realization of an sequence pseudo-random multi-frequencies signal","volume":"40","author":"He","year":"2009","journal-title":"J. Cent. South Univ."},{"key":"mlstad0c40bib4","first-page":"2459","article-title":"Three-dimensional modeling for E-Ex wide field electromagnetic methods","volume":"23","author":"Li","year":"2013","journal-title":"Trans. Nonferrous Met. Soc."},{"key":"mlstad0c40bib5","first-page":"2422","article-title":"Exploration of various electromagnetic method in some gold mine","volume":"23","author":"Liu","year":"2013","journal-title":"Trans. Nonferrous Met. Soc."},{"key":"mlstad0c40bib6","first-page":"1006","article-title":"Shale gas detection with wide field electromagnetic method in North-western Hunan","volume":"49","author":"He","year":"2014","journal-title":"Oil Geophys. Prospect."},{"key":"mlstad0c40bib7","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1007\/s11770-017-0633-x","article-title":"Application of a wide-field electromagnetic method to shale gas exploration in South China","volume":"14","author":"Yang","year":"2017","journal-title":"Appl. Geophys."},{"key":"mlstad0c40bib8","first-page":"1085","article-title":"Application of wide field electromagnetic method to the hydrocarbon exploration in a basin of South Jiangxi","volume":"52","author":"Zhang","year":"2017","journal-title":"Oil Geophys. Prospect."},{"key":"mlstad0c40bib9","doi-asserted-by":"publisher","first-page":"2087","DOI":"10.6038\/cjg20150623","article-title":"A new method for handling gross errors in electromagnetic prospecting data","volume":"58","author":"Zhang","year":"2015","journal-title":"Chin. J. Geophys."},{"key":"mlstad0c40bib10","doi-asserted-by":"publisher","first-page":"570","DOI":"10.1007\/s11770-017-0646-5","article-title":"Controlled-source electromagnetic data processing based on gray system theory and robust estimation","volume":"14","author":"Mo","year":"2017","journal-title":"Appl. Geophys."},{"key":"mlstad0c40bib11","doi-asserted-by":"publisher","first-page":"3854","DOI":"10.6038\/cjg2019M0415","article-title":"De-noising pseudo-random electromagnetic data using gray judgment criterion and rational function filtering","volume":"62","author":"Chen","year":"2019","journal-title":"Chin. J. Geophys."},{"key":"mlstad0c40bib12","doi-asserted-by":"publisher","first-page":"344","DOI":"10.6038\/cjg2018L0298","article-title":"A noise evaluation method for CSEM in the frequency domain based on wavelet transform and analytic envelope","volume":"61","author":"Yang","year":"2018","journal-title":"Chin. J. Geophys."},{"key":"mlstad0c40bib13","doi-asserted-by":"publisher","first-page":"E229","DOI":"10.1190\/geo2016-0659.1","article-title":"Denoising controlled-source electromagnetic data using least-squares inversion","volume":"83","author":"Yang","year":"2018","journal-title":"Geophysics"},{"key":"mlstad0c40bib14","doi-asserted-by":"publisher","first-page":"E185","DOI":"10.1190\/geo2020-0246.1","article-title":"Dictionary learning and shift-invariant sparse coding denoising for controlled-source electromagnetic data combined with complementary ensemble empirical mode decomposition","volume":"86","author":"Li","year":"2021","journal-title":"Geophysics"},{"key":"mlstad0c40bib15","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1093\/jge\/gxab018","article-title":"Application of powerline noise cancellation method in correlation identification of controlled source electromagnetic method","volume":"18","author":"Yang","year":"2021","journal-title":"J. Geophys. Eng."},{"key":"mlstad0c40bib16","doi-asserted-by":"publisher","first-page":"2150","DOI":"10.1007\/s11771-022-5180-9","article-title":"Extracting useful high-frequency information from wide-field electromagnetic data using time-domain signal reconstruction","volume":"29","author":"Ling","year":"2022","journal-title":"J. Cent. South Univ."},{"key":"mlstad0c40bib17","doi-asserted-by":"publisher","first-page":"E107","DOI":"10.1190\/geo2022-0317.1","article-title":"IncepTCN: a new deep temporal convolutional network combined with dictionary learning for strong cultural noise elimination of controlled-source electromagnetic data","volume":"88","author":"Li","year":"2023","journal-title":"Geophysics"},{"key":"mlstad0c40bib18","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.64.011114","article-title":"Effect of trends on detrended fluctuation analysis","volume":"64","author":"Hu","year":"2001","journal-title":"Phys. Rev. E"},{"key":"mlstad0c40bib19","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1016\/0378-4371(95)00247-5","article-title":"Statistical properties of DNA sequences","volume":"221","author":"Peng","year":"2008","journal-title":"Physica A"},{"key":"mlstad0c40bib20","doi-asserted-by":"publisher","DOI":"10.1016\/j.cageo.2021.104794","article-title":"Effect of missing data on short time series and their application in the characterization of surface temperature by detrended fluctuation analysis","volume":"153","author":"L\u00f3pez","year":"2021","journal-title":"Comput. Geosci."},{"key":"mlstad0c40bib21","doi-asserted-by":"publisher","DOI":"10.1016\/j.jappgeo.2020.104127","article-title":"Noise suppression for magnetotelluric using variational mode decomposition and detrended fluctuation analysis","volume":"180","author":"Li","year":"2020","journal-title":"J. Appl. Geophys."},{"key":"mlstad0c40bib22","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1098\/rspa.2006.1761","article-title":"Intrinsic time-scale decomposition: time frequency-energy analysis and real-time filtering of non-stationary signals","volume":"463","author":"Frei","year":"2007","journal-title":"Proc. R. Soc. A"},{"key":"mlstad0c40bib23","first-page":"954","article-title":"Based on the improved ITD and energy moment to diagnose the gear","volume":"33","author":"Chen","year":"2013","journal-title":"J. Vib. Meas. Diagn."},{"key":"mlstad0c40bib24","doi-asserted-by":"publisher","DOI":"10.1088\/0957-0233\/26\/2\/025003","article-title":"A fault diagnosis approach for diesel engine valve train based on improved ITD and SDAG-RVM","volume":"26","author":"Yu","year":"2015","journal-title":"Meas. Sci. Technol."},{"key":"mlstad0c40bib25","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1016\/j.dsp.2014.06.006","article-title":"Detrended fluctuation thresholding for empirical mode decomposition based de-noising","volume":"32","author":"Mert","year":"2014","journal-title":"Digit. Signal Process."},{"key":"mlstad0c40bib26","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1007\/s11600-021-00714-2","article-title":"Grey wolf optimization-based variational mode decomposition for magnetotelluric data combined with detrended fluctuation analysis","volume":"70","author":"Zhang","year":"2022","journal-title":"Acta Geophys."},{"key":"mlstad0c40bib27","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2020.113609","article-title":"The arithmetic optimization algorithm","volume":"376","author":"Abualigah","year":"2021","journal-title":"Comput. Methods Appl. Mech. Eng."},{"key":"mlstad0c40bib28","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.104981","article-title":"An opposition learning and spiral modelling based arithmetic optimization algorithm for global continuous optimization problems","volume":"113","author":"Yang","year":"2022","journal-title":"Eng. Appl. Artif. Intell."},{"key":"mlstad0c40bib29","doi-asserted-by":"crossref","DOI":"10.1109\/ICNN.1995.488968","article-title":"Particle swarm optimization","author":"Kennedy","year":"1995"},{"key":"mlstad0c40bib30","doi-asserted-by":"publisher","first-page":"459","DOI":"10.1007\/s10898-007-9149-x","article-title":"A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm","volume":"39","author":"Karaboga","year":"2007","journal-title":"J. Glob. Optim."},{"key":"mlstad0c40bib31","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1007\/s00521-015-1870-7","article-title":"Multi-verse optimizer: a nature-inspired algorithm for global optimization","volume":"27","author":"Mirjalili","year":"2015","journal-title":"Neural Comput. Appl."},{"key":"mlstad0c40bib32","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1016\/j.knosys.2015.07.006","article-title":"Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm","volume":"89","author":"Mirjalili","year":"2015","journal-title":"Knowl.-Based Syst."},{"key":"mlstad0c40bib33","doi-asserted-by":"publisher","first-page":"1215","DOI":"10.1111\/1365-2478.12640","article-title":"Grey wolf optimizer: a new strategy to invert geophysical data sets","volume":"66","author":"Agarwal","year":"2017","journal-title":"Geophys. Prospect."},{"key":"mlstad0c40bib34","doi-asserted-by":"publisher","first-page":"80","DOI":"10.3390\/fractalfract6020080","article-title":"Signal-noise identification for wide field electromagnetic method data using multi-domain features and IGWO-SVM","volume":"6","author":"Zhang","year":"2022","journal-title":"Fractal Fract."},{"key":"mlstad0c40bib35","doi-asserted-by":"publisher","first-page":"12118","DOI":"10.3390\/rs61212118","article-title":"Delineation of rain areas with TRMM microwave observations based on PNN","volume":"6","author":"Xu","year":"2014","journal-title":"Remote Sens."},{"key":"mlstad0c40bib36","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/j.gsf.2014.10.005","article-title":"Computer vision-based limestone rock-type classification using probabilistic neural network","volume":"7","author":"Patel","year":"2016","journal-title":"Geosci. Front."},{"key":"mlstad0c40bib37","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1109\/72.88165","article-title":"Learning vector quantization for the probabilistic neural network","volume":"2","author":"Burrascano","year":"1991","journal-title":"IEEE Trans. Neural Netw."},{"key":"mlstad0c40bib38","doi-asserted-by":"publisher","first-page":"18084","DOI":"10.1021\/acsomega.1c01878","article-title":"Novel probabilistic neural network models combined with dissolved gas analysis for fault diagnosis of oil-immersed power transformers","volume":"6","author":"Zhou","year":"2021","journal-title":"ACS Omega"}],"container-title":["Machine Learning: Science and Technology"],"original-title":[],"link":[{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2632-2153\/ad0c40","content-type":"text\/html","content-version":"am","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2632-2153\/ad0c40\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2632-2153\/ad0c40","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2632-2153\/ad0c40\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2632-2153\/ad0c40\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2632-2153\/ad0c40\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2632-2153\/ad0c40\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"similarity-checking"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2632-2153\/ad0c40\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T05:46:18Z","timestamp":1701323178000},"score":1,"resource":{"primary":{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2632-2153\/ad0c40"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,30]]},"references-count":38,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,11,30]]},"published-print":{"date-parts":[[2023,12,1]]}},"URL":"https:\/\/doi.org\/10.1088\/2632-2153\/ad0c40","relation":{},"ISSN":["2632-2153"],"issn-type":[{"value":"2632-2153","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,30]]},"assertion":[{"value":"Intelligent processing of electromagnetic data using detrended and identification","name":"article_title","label":"Article Title"},{"value":"Machine Learning: Science and Technology","name":"journal_title","label":"Journal Title"},{"value":"paper","name":"article_type","label":"Article Type"},{"value":"\u00a9 2023 The Author(s). Published by IOP Publishing Ltd","name":"copyright_information","label":"Copyright Information"},{"value":"2023-06-22","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2023-11-13","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2023-11-30","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}