{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T17:02:06Z","timestamp":1780419726395,"version":"3.54.1"},"reference-count":47,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100004735","name":"Natural Science Foundation of Hunan Province","doi-asserted-by":"publisher","award":["2024JJ2074"],"award-info":[{"award-number":["2024JJ2074"]}],"id":[{"id":"10.13039\/501100004735","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002822","name":"Central South University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002822","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["22376221"],"award-info":[{"award-number":["22376221"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Applied Soft Computing"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.asoc.2026.115281","type":"journal-article","created":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T15:28:05Z","timestamp":1776526085000},"page":"115281","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["An encoder-only transformer model for predicting soil temperature from time series data"],"prefix":"10.1016","volume":"198","author":[{"given":"Mohammad Sadegh","family":"Barkhordari","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad Mahdi","family":"Barkhordari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chongchong","family":"Qi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"4","key":"10.1016\/j.asoc.2026.115281_bib1","first-page":"1","article-title":"Influence of soil temperature on root development and microbial diversity in paddy fields: a comprehensive review","volume":"2","author":"Patah","year":"2024","journal-title":"Trends Ecol. Indoor Environ. Eng."},{"issue":"1","key":"10.1016\/j.asoc.2026.115281_bib2","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/S2095-3119(19)62657-2","article-title":"Soil temperature estimation at different depths, using remotely-sensed data","volume":"19","author":"Huang","year":"2020","journal-title":"J. Integr. Agric."},{"key":"10.1016\/j.asoc.2026.115281_bib3","doi-asserted-by":"crossref","first-page":"2025","DOI":"10.3389\/fagro.2025.1496198","article-title":"Understanding the impact of irrigation scheduling on water use efficiency in corn and soybean production in humid climates: insights from on-farm demonstration","volume":"7","author":"Kelley","year":"2025","journal-title":"Front. Agron."},{"issue":"4","key":"10.1016\/j.asoc.2026.115281_bib4","doi-asserted-by":"crossref","DOI":"10.1029\/2021EF002377","article-title":"The role of soil temperature feedbacks for summer air temperature variability under climate change over East Asia","volume":"10","author":"Li","year":"2022","journal-title":"Earth's. Future"},{"key":"10.1016\/j.asoc.2026.115281_bib5","article-title":"Surface soil temperature seasonal variation estimation in a forested area using combined satellite observations and in-situ measurements","volume":"91","author":"Xu","year":"2020","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"issue":"2","key":"10.1016\/j.asoc.2026.115281_bib6","doi-asserted-by":"crossref","first-page":"203","DOI":"10.2166\/wcc.2017.027","article-title":"Predicting soil temperature by applying atmosphere general circulation data in west Iran","volume":"8","author":"Maryanaji","year":"2017","journal-title":"J. Water Clim. Change"},{"issue":"12","key":"10.1016\/j.asoc.2026.115281_bib7","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0293751","article-title":"Development of a robust daily soil temperature estimation in semi-arid continental climate using meteorological predictors based on computational intelligent paradigms","volume":"18","author":"Alizamir","year":"2023","journal-title":"PLOS ONE"},{"issue":"9","key":"10.1016\/j.asoc.2026.115281_bib8","article-title":"A review of machine learning approaches to soil temperature estimation","volume":"15","author":"Taheri","year":"2023","journal-title":"Sustain. [Internet]"},{"key":"10.1016\/j.asoc.2026.115281_bib9","unstructured":"Deshpande G., Goswami M., Kolhe J., Khandagale V., Khope D., Patel G., et al. IoT-Based Low-Cost Soil Moisture and Soil Temperature Monitoring System. arXiv preprint arXiv:220607488. 2022."},{"issue":"12","key":"10.1016\/j.asoc.2026.115281_bib10","doi-asserted-by":"crossref","first-page":"16398","DOI":"10.3390\/rs71215841","article-title":"Review of machine learning approaches for biomass and soil moisture retrievals from remote sensing data","volume":"7","author":"Ali","year":"2015","journal-title":"Remote Sens. [Internet]"},{"issue":"4","key":"10.1016\/j.asoc.2026.115281_bib11","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1016\/j.advwatres.2010.01.011","article-title":"Effect of simultaneous state\u2013parameter estimation and forcing uncertainties on root-zone soil moisture for dynamic vegetation using EnKF","volume":"33","author":"Monsivais-Huertero","year":"2010","journal-title":"Adv. Water Resour."},{"issue":"5","key":"10.1016\/j.asoc.2026.115281_bib12","doi-asserted-by":"crossref","DOI":"10.1002\/vzj2.20151","article-title":"Knowledge-guided machine learning for improving daily soil temperature prediction across the United States","volume":"20","author":"Abimbola","year":"2021","journal-title":"Vadose Zone J."},{"issue":"2","key":"10.1016\/j.asoc.2026.115281_bib13","article-title":"Adjusting soil temperatures with a physics-informed deep learning model for a high-resolution numerical weather prediction system","volume":"16","author":"Wang","year":"2025","journal-title":"Atmosphere [Internet]"},{"key":"10.1016\/j.asoc.2026.115281_bib14","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.still.2018.12.023","article-title":"A reliable linear stochastic daily soil temperature forecast model","volume":"189","author":"Zeynoddin","year":"2019","journal-title":"Soil Tillage Res."},{"issue":"4","key":"10.1016\/j.asoc.2026.115281_bib15","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0231055","article-title":"Advanced machine learning model for better prediction accuracy of soil temperature at different depths","volume":"15","author":"Alizamir","year":"2020","journal-title":"PLOS ONE"},{"key":"10.1016\/j.asoc.2026.115281_bib16","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2025.178901","article-title":"A spatiotemporal CNN-LSTM deep learning model for predicting soil temperature in diverse large-scale regional climates","volume":"968","author":"Farhangmehr","year":"2025","journal-title":"Sci. Total Environ."},{"key":"10.1016\/j.asoc.2026.115281_bib17","doi-asserted-by":"crossref","DOI":"10.1016\/j.geoderma.2021.115651","article-title":"An attention-aware LSTM model for soil moisture and soil temperature prediction","volume":"409","author":"Li","year":"2022","journal-title":"Geoderma"},{"issue":"1","key":"10.1016\/j.asoc.2026.115281_bib18","doi-asserted-by":"crossref","first-page":"1535","DOI":"10.1038\/s41598-023-48025-4","article-title":"Soil temperature forecasting using a hybrid artificial neural network in Florida subtropical grazinglands agro-ecosystems","volume":"14","author":"Biazar","year":"2024","journal-title":"Sci. Rep."},{"issue":"10","key":"10.1016\/j.asoc.2026.115281_bib19","article-title":"A convolutional neural network model for soil temperature prediction under ordinary and hot weather conditions: comparison with a multilayer perceptron model","volume":"15","author":"Farhangmehr","year":"2023","journal-title":"Sustain. [Internet]"},{"key":"10.1016\/j.asoc.2026.115281_bib20","doi-asserted-by":"crossref","first-page":"2024","DOI":"10.3389\/fpls.2024.1460654","article-title":"A multivariate soil temperature interval forecasting method for precision regulation of plant growth environment","volume":"15","author":"Yin","year":"2024","journal-title":"Front. Plant Sci."},{"issue":"15","key":"10.1016\/j.asoc.2026.115281_bib21","doi-asserted-by":"crossref","first-page":"2347","DOI":"10.1080\/00103624.2025.2510492","article-title":"Predicting daily soil temperature at 50 Cm depth using advanced hybrid and combined models in semi-arid regions","volume":"56","author":"Sharafi","year":"2025","journal-title":"Commun. Soil Sci. Plant Anal."},{"key":"10.1016\/j.asoc.2026.115281_bib22","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2021.112605","article-title":"Evaluation of six satellite- and model-based surface soil temperature datasets using global ground-based observations","volume":"264","author":"Ma","year":"2021","journal-title":"Remote Sens. Environ."},{"issue":"8","key":"10.1016\/j.asoc.2026.115281_bib23","doi-asserted-by":"crossref","first-page":"962","DOI":"10.1007\/s10661-023-11566-2","article-title":"Extreme learning machine for soil temperature prediction using only air temperature as input","volume":"195","author":"Belouz","year":"2023","journal-title":"Environ. Monit. Assess."},{"issue":"9","key":"10.1016\/j.asoc.2026.115281_bib24","article-title":"Feature selection methods for extreme learning machines","volume":"11","author":"Fu","year":"2022","journal-title":"Axioms [Internet]"},{"key":"10.1016\/j.asoc.2026.115281_bib25","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2021.106158","article-title":"Modeling soil temperature using air temperature features in diverse climatic conditions with complementary machine learning models","volume":"185","author":"Bayatvarkeshi","year":"2021","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.asoc.2026.115281_bib26","doi-asserted-by":"crossref","unstructured":"Phan D.T., editor Reduce Computational Complexity For Continuous Wavelet Transform in Acoustic Recognition Using Hop Size. 2024 International Symposium on Electronics and Telecommunications (ISETC); 2024 7\u20138 Nov. 2024. \u3008https:\/\/doi.org\/10.1109\/ISETC63109.2024.10797444\u3009.","DOI":"10.1109\/ISETC63109.2024.10797444"},{"issue":"3","key":"10.1016\/j.asoc.2026.115281_bib27","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1016\/j.pedsph.2022.06.056","article-title":"Multi-step ahead soil temperature forecasting at different depths based on meteorological data: integrating resampling algorithms and machine learning models","volume":"33","author":"Khosravi","year":"2023","journal-title":"Pedosphere"},{"issue":"12","key":"10.1016\/j.asoc.2026.115281_bib28","doi-asserted-by":"crossref","first-page":"3568","DOI":"10.1016\/j.enbuild.2011.09.026","article-title":"Estimation of soil temperature profile in Hong Kong from climatic variables","volume":"43","author":"Chow","year":"2011","journal-title":"Energy Build."},{"issue":"1","key":"10.1016\/j.asoc.2026.115281_bib29","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-025-04605-0","article-title":"Investigating the impact of meteorological parameters on daily soil temperature changes using machine learning models","volume":"15","author":"Asadzadeh","year":"2025","journal-title":"Sci. Rep."},{"key":"10.1016\/j.asoc.2026.115281_bib30","doi-asserted-by":"crossref","DOI":"10.1016\/j.agrformet.2020.107912","article-title":"Gap-filling continuously-measured soil respiration data: a highlight of time-series-based methods","volume":"285-286","author":"Zhao","year":"2020","journal-title":"Agric. For. Meteorol."},{"key":"10.1016\/j.asoc.2026.115281_bib31","doi-asserted-by":"crossref","DOI":"10.1016\/j.jhydrol.2025.132762","article-title":"Global-scale gap filling of satellite soil moisture products: methods and validation","volume":"653","author":"Zhang","year":"2025","journal-title":"J. Hydrol."},{"key":"10.1016\/j.asoc.2026.115281_bib32","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1007\/s13253-019-00372-4","article-title":"Efficient reconstructions of common era climate via integrated nested Laplace approximations","volume":"24","author":"Barboza","year":"2019","journal-title":"J. Agric. Biol. Environ. Stat."},{"key":"10.1016\/j.asoc.2026.115281_bib33","unstructured":"Sun E., Lin K.-hE., Tseng W.-L., Wang P.K., Huang H.-C. Reconstructing East Asian Temperatures from 1368 to 1911 Using Historical Documents, Climate Models, and Data Assimilation. arXiv preprint arXiv:241021790. 2024."},{"key":"10.1016\/j.asoc.2026.115281_bib34","doi-asserted-by":"crossref","DOI":"10.1016\/j.istruc.2023.105277","article-title":"Enhanced data imputation framework for bridge health monitoring using Wasserstein generative adversarial networks with gradient penalty","volume":"57","author":"Gao","year":"2023","journal-title":"Structures"},{"issue":"4","key":"10.1016\/j.asoc.2026.115281_bib35","article-title":"Beyond ensemble averages: leveraging climate model ensembles for subseasonal forecasting","volume":"3","author":"Orlova","year":"2024","journal-title":"Artif. Intell. Earth Syst."},{"key":"10.1016\/j.asoc.2026.115281_bib36","doi-asserted-by":"crossref","DOI":"10.1007\/s00330-025-11637-7","article-title":"Multicollinearity and redundancy of the PET radiomic feature set","author":"Noortman","year":"2025","journal-title":"Eur. Radio."},{"issue":"1","key":"10.1016\/j.asoc.2026.115281_bib37","article-title":"Analysis of the application of different forecasting methods for time series in the context of the aeronautical industry","volume":"39","author":"de Camargo","year":"2023","journal-title":"Eng. Proc. [Internet]"},{"issue":"1","key":"10.1016\/j.asoc.2026.115281_bib38","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/j.ijforecast.2003.09.015","article-title":"Forecasting seasonals and trends by exponentially weighted moving averages","volume":"20","author":"Holt","year":"2004","journal-title":"Int. J. Forecast."},{"key":"10.1016\/j.asoc.2026.115281_bib39","doi-asserted-by":"crossref","DOI":"10.1504\/IJOR.2025.143957","article-title":"MSTL: a seasonal-trend decomposition algorithm for time series with multiple seasonal patterns","author":"Bandara","year":"2025","journal-title":"Int. J. Oper. Res."},{"key":"10.1016\/j.asoc.2026.115281_bib40","unstructured":"Jiang X., Jiang M., Zhou Q. Day-Ahead PV Power Forecasting Based on MSTL-TFT. arXiv preprint arXiv:230105911. 2023."},{"issue":"4","key":"10.1016\/j.asoc.2026.115281_bib41","doi-asserted-by":"crossref","first-page":"2571","DOI":"10.1007\/s00704-023-04781-x","article-title":"A comparative analysis of deep learning models for soil temperature prediction in cold climates","volume":"155","author":"Imanian","year":"2024","journal-title":"Theor. Appl. Climatol."},{"key":"10.1016\/j.asoc.2026.115281_bib42","series-title":"2023 IEEE International Conference on Contemporary Computing and Communications (InC4)","article-title":"Analytical methods of machine learning model for e-commerce sales analysis and prediction","author":"Xavier","year":"2023"},{"key":"10.1016\/j.asoc.2026.115281_bib43","unstructured":"Chung Y., Neiswanger W., Char I., Schneider J.G. Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification. ArXiv. 2020. \u3008https:\/\/doi.org\/10.48550\/arXiv.2011.09588\u3009."},{"issue":"2","key":"10.1016\/j.asoc.2026.115281_bib44","article-title":"Soil temperature prediction based on ensemble tree bagger machine learning algorithm for agricultural decision making","volume":"12","author":"Alagesan","year":"2025","journal-title":"Plant Sci. Today"},{"key":"10.1016\/j.asoc.2026.115281_bib45","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.geoderma.2018.11.044","article-title":"Estimation of soil temperature from meteorological data using different machine learning models","volume":"338","author":"Feng","year":"2019","journal-title":"Geoderma"},{"key":"10.1016\/j.asoc.2026.115281_bib46","doi-asserted-by":"crossref","unstructured":"Toomani P., Khosravi M., Nazemi N., Khosravi A., Dadgostari F., Sherazi S.H.A. Ground Temperature Prediction Using Physics-Informed Machine Learning Modeling Approach: Unraveling Key Predictive Factors. Available at SSRN 4991188. 2024. \u3008https:\/\/dx.doi.org\/10.2139\/ssrn.4991188\u3009.","DOI":"10.2139\/ssrn.4991188"},{"issue":"6","key":"10.1016\/j.asoc.2026.115281_bib47","doi-asserted-by":"crossref","first-page":"2643","DOI":"10.2166\/hydro.2023.188","article-title":"Enhanced forecasting of multi-step ahead daily soil temperature using advanced hybrid vote algorithm-based tree models","volume":"25","author":"Hatamiafkoueieh","year":"2023","journal-title":"J. Hydroinformatics"}],"container-title":["Applied Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494626007295?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494626007295?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T16:01:44Z","timestamp":1780416104000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1568494626007295"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":47,"alternative-id":["S1568494626007295"],"URL":"https:\/\/doi.org\/10.1016\/j.asoc.2026.115281","relation":{},"ISSN":["1568-4946"],"issn-type":[{"value":"1568-4946","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"An encoder-only transformer model for predicting soil temperature from time series data","name":"articletitle","label":"Article Title"},{"value":"Applied Soft Computing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.asoc.2026.115281","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"115281"}}