{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T13:06:06Z","timestamp":1770987966259,"version":"3.50.1"},"reference-count":32,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2023,9,8]],"date-time":"2023-09-08T00:00:00Z","timestamp":1694131200000},"content-version":"vor","delay-in-days":69,"URL":"https:\/\/2.zoppoz.workers.dev:443\/http\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Information Sciences"],"published-print":{"date-parts":[[2023,7]]},"DOI":"10.1016\/j.ins.2023.03.117","type":"journal-article","created":{"date-parts":[[2023,3,22]],"date-time":"2023-03-22T00:12:39Z","timestamp":1679443959000},"page":"677-695","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":4,"special_numbering":"C","title":["A novel spatiotemporal prediction method based on fuzzy Transform: Application to demographic balance data"],"prefix":"10.1016","volume":"634","author":[{"given":"Barbara","family":"Cardone","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ferdinando","family":"Di Martino","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.ins.2023.03.117_b0005","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.wasman.2016.05.018","article-title":"Forecasting municipal solid waste generation using artificial intelligence modelling approaches","volume":"56","author":"Abbasi","year":"2016","journal-title":"Waste Manage."},{"key":"10.1016\/j.ins.2023.03.117_b0010","doi-asserted-by":"crossref","unstructured":"Adi Maimun N. H., Ismail S.,Junainah M.,Razali M. N.,Tarmidi M. Z., Idris H. (2018) An integrated framework for affordable housing demand projection and site selection, 2018 IOP Conference Series: Earth and Environmental Science, 169 012094.","DOI":"10.1088\/1755-1315\/169\/1\/012094"},{"key":"10.1016\/j.ins.2023.03.117_b0015","doi-asserted-by":"crossref","first-page":"22243","DOI":"10.1038\/s41598-020-79148-7","article-title":"A novel framework for spatio-temporal prediction of environmental data using deep learning","volume":"10","author":"Amato","year":"2020","journal-title":"Sci Rep"},{"key":"10.1016\/j.ins.2023.03.117_b0020","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.ijar.2019.05.002","article-title":"Designing fuzzy time series forecasting models: A survey","volume":"111","author":"Bose","year":"2019","journal-title":"Int. J. Approx. Reason."},{"issue":"1","key":"10.1016\/j.ins.2023.03.117_b0025","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"10.1016\/j.ins.2023.03.117_b0030","doi-asserted-by":"crossref","unstructured":"Breiman L., Friedman J.H., Olshen R.A., Stone C.J. (2017). Classification and regression trees. New York: Routledge. Chapter 4, 368 pp., doi: 10.1201\/9781315139470.","DOI":"10.1201\/9781315139470"},{"key":"10.1016\/j.ins.2023.03.117_b0035","doi-asserted-by":"crossref","first-page":"370","DOI":"10.3390\/electronics11030370","article-title":"Fuzzy-Based Spatiotemporal Hot Spot Intensity and Propagation - An Application in Crime Analysis","volume":"11","author":"Cardone","year":"2022","journal-title":"Electronics"},{"key":"10.1016\/j.ins.2023.03.117_b0040","doi-asserted-by":"crossref","unstructured":"Carvalho Jr I.J., Costa Jr C.T. (1017) Identification method for fuzzy forecasting models of time series, Applied Soft Computing, 50, 166-182, doi: 10.1016\/j.asoc.2016.11.003.","DOI":"10.1016\/j.asoc.2016.11.003"},{"key":"10.1016\/j.ins.2023.03.117_b0045","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1016\/j.ins.2009.10.012","article-title":"Fuzzy transforms method and attribute dependency in data analysis","volume":"180","author":"Di Martino","year":"2010","journal-title":"Inf. Sci."},{"key":"10.1016\/j.ins.2023.03.117_b0050","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.fss.2010.11.009","article-title":"Fuzzy transforms method in prediction data analysis","volume":"180","author":"Di Martino","year":"2011","journal-title":"Fuzzy Set. Syst."},{"key":"10.1016\/j.ins.2023.03.117_b0055","doi-asserted-by":"crossref","first-page":"3537","DOI":"10.1007\/s00500-017-2621-8","article-title":"Fuzzy transforms prediction in spatial analysis and its application to demographic balance data","volume":"21","author":"Di Martino","year":"2017","journal-title":"Soft. Comput."},{"issue":"2","key":"10.1016\/j.ins.2023.03.117_b0060","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1080\/10106049.2019.1595177","article-title":"Geographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling","volume":"36","author":"Georganos","year":"2021","journal-title":"Geocarto Int."},{"key":"10.1016\/j.ins.2023.03.117_b0065","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.aap.2016.08.015","article-title":"A New Integrated GIS-based Analysis to Detect hot spots: A Case Study of the City of Sherbrooke","volume":"130","author":"Harirforoush","year":"2019","journal-title":"Accid. Anal. Prev."},{"key":"10.1016\/j.ins.2023.03.117_b0070","doi-asserted-by":"crossref","first-page":"e5518","DOI":"10.7717\/peerj.5518","article-title":"Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables","volume":"6","author":"Hengl","year":"2018","journal-title":"PeerJ"},{"key":"10.1016\/j.ins.2023.03.117_b0075","doi-asserted-by":"crossref","unstructured":"Hyndman R. J., Koehler A., Ord K., Snyder R. (2008). Forecasting with Exponential Smoothing. The State Space Approach, Springer Series in Statistics, Springer, Heidemberg, 362 pp., doi: 10.1007\/978-3-540-71918-2.","DOI":"10.1007\/978-3-540-71918-2"},{"issue":"3","key":"10.1016\/j.ins.2023.03.117_b0080","first-page":"1","article-title":"Automatic time series forecasting: the forecast package for R","volume":"26","author":"Hyndman","year":"2008","journal-title":"J. Stat. Softw."},{"issue":"19","key":"10.1016\/j.ins.2023.03.117_b0085","doi-asserted-by":"crossref","first-page":"6726","DOI":"10.3390\/app10196726","article-title":"Hybrid Fuzzy Regression Analysis Using the F-Transform","volume":"10","author":"Jung","year":"2020","journal-title":"Appl. Sci."},{"key":"10.1016\/j.ins.2023.03.117_b0090","unstructured":"Klosterman R. E., Brooks, K., Drucker, J., Feser, E., & Renski, H. (2018).Planning support methods: Urban and regional analysis and projection. Rowman & Littlefield, 320 pp. ISBN: 1442220309."},{"issue":"2","key":"10.1016\/j.ins.2023.03.117_b0095","first-page":"29","article-title":"A Tutorial on Fuzzy Time Series Forecasting models: recent advances and challenges.Learning and Nonlinear Models","volume":"19","author":"Lucas","year":"2021","journal-title":"J. Braz. Soc. Comput. Intell."},{"key":"10.1016\/j.ins.2023.03.117_b0100","doi-asserted-by":"crossref","unstructured":"Lucas P. O., Alves M. A., de Lima e Silva P. C., Gadelha Guimar\u00e3es F. (2020) Reference evapotranspiration time series forecasting with ensemble of convolutional neural networks. Computers and electronics in agriculture, 177, 105700, Computers and electronics in agriculture 2020 v.177, doi:10.1016\/j.compag.2020.105700. Learning and Nonlinear Models - Journal of the Brazilian Society on Computational Intelligence, 19(2) 29-50, doi:10.21528\/lnlm-vol19-no2-art3.","DOI":"10.21528\/lnlm-vol19-no2-art3"},{"key":"10.1016\/j.ins.2023.03.117_b0105","doi-asserted-by":"crossref","unstructured":"Mishra B. P., Ghose D. K., Satapathy D. P., Ghose, S. (2022). Flood Susceptibility Modeling Using Forest-Based Regression. In: Udgata, S.K., Sethi, S., Gao, XZ. (eds) Intelligent Systems. Lecture Notes in Networks and Systems, vol 431. Springer, Singapore, doi: 10.1007\/978-981-19-0901-6_51.","DOI":"10.1007\/978-981-19-0901-6_51"},{"key":"10.1016\/j.ins.2023.03.117_b0110","doi-asserted-by":"crossref","first-page":"5287","DOI":"10.1007\/s10708-022-10573-z","article-title":"Crime hotspot detection using statistical and geospatial methods: a case study of Pune City, Maharashtra, India","volume":"87","author":"Mondal","year":"2022","journal-title":"GeoJournal"},{"key":"10.1016\/j.ins.2023.03.117_b0120","article-title":"A combined robust fuzzy time series method for prediction of time series","volume":"1010","author":"Naresh","year":"2021","journal-title":"Appl. Soft Comput."},{"issue":"14","key":"10.1016\/j.ins.2023.03.117_b0125","doi-asserted-by":"crossref","first-page":"6894","DOI":"10.3390\/app12146894","article-title":"Fuzzy-Based Time Series Forecasting and Modelling: A Bibliometric Analysis","volume":"12","author":"Palomero","year":"2022","journal-title":"Appl. Sci."},{"key":"10.1016\/j.ins.2023.03.117_b0130","first-page":"641","article-title":"Fuzzy Time Series Forecasting: A Survey","volume":"vol 990","author":"Panigrahi","year":"2020"},{"issue":"4","key":"10.1016\/j.ins.2023.03.117_b0135","doi-asserted-by":"crossref","first-page":"975","DOI":"10.3390\/su11040975","article-title":"Combining Artificial Neural Networks and GIS Fundamentals for Coastal Erosion Prediction Modeling","volume":"11","author":"Peponi","year":"2019","journal-title":"Sustainability"},{"key":"10.1016\/j.ins.2023.03.117_b0140","doi-asserted-by":"crossref","first-page":"993","DOI":"10.1016\/j.fss.2005.11.012","article-title":"Fuzzy transforms: theory and applications","volume":"157","author":"Perfilieva","year":"2006","journal-title":"Fuzzy Set. Syst."},{"key":"10.1016\/j.ins.2023.03.117_b0145","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.fss.2021.09.009","article-title":"An approach for evolving neuro-fuzzy forecasting of time series based on parallel recursive singular spectrum analysis","volume":"443","author":"Rodrigues-J\u00fanior","year":"2021","journal-title":"Fuzzy Set. Syst."},{"key":"10.1016\/j.ins.2023.03.117_b0150","first-page":"5","article-title":"Detecting Hot Spots on Crime Data Using Data Mining and Geographical Information System","volume":"8","author":"Sing","year":"2013","journal-title":"Int. J. Stat. Math."},{"issue":"2","key":"10.1016\/j.ins.2023.03.117_b0155","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1080\/13683500.2018.1491955","article-title":"Distribution of tourists within urban heritage destinations: a hot spot\/cold spot analysis of TripAdvisor data as support for destination management","volume":"23","author":"van der Zee","year":"2020","journal-title":"Curr. Issue Tour."},{"key":"10.1016\/j.ins.2023.03.117_b0160","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.wasman.2019.03.037","article-title":"Assessment of waste features and their impact on GIS vehicle collection route optimization using ANN waste forecasts","volume":"88","author":"Vu","year":"2019","journal-title":"Waste Manag."},{"issue":"110","key":"10.1016\/j.ins.2023.03.117_b0115","article-title":"Particle swarm optimization of partitions and fuzzy order for fuzzy time series forecasting of COVID-19","volume":"221","author":"Naresh","year":"2021","journal-title":"Appl. Soft Comput."}],"container-title":["Information Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/api.elsevier.com\/content\/article\/PII:S0020025523004425?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/api.elsevier.com\/content\/article\/PII:S0020025523004425?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T06:09:46Z","timestamp":1758089386000},"score":1,"resource":{"primary":{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/linkinghub.elsevier.com\/retrieve\/pii\/S0020025523004425"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7]]},"references-count":32,"alternative-id":["S0020025523004425"],"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/j.ins.2023.03.117","relation":{},"ISSN":["0020-0255"],"issn-type":[{"value":"0020-0255","type":"print"}],"subject":[],"published":{"date-parts":[[2023,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A novel spatiotemporal prediction method based on fuzzy Transform: Application to demographic balance data","name":"articletitle","label":"Article Title"},{"value":"Information Sciences","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/j.ins.2023.03.117","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2023 The Authors. Published by Elsevier Inc.","name":"copyright","label":"Copyright"}]}}