{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T19:55:54Z","timestamp":1760730954417,"version":"3.37.3"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2017,6,24]],"date-time":"2017-06-24T00:00:00Z","timestamp":1498262400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2018,4]]},"DOI":"10.1007\/s00521-017-3125-2","type":"journal-article","created":{"date-parts":[[2017,6,24]],"date-time":"2017-06-24T09:58:56Z","timestamp":1498298336000},"page":"375-388","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["FuSSFFra, a fuzzy semi-supervised forecasting framework: the case of the air pollution in Athens"],"prefix":"10.1007","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1330-5228","authenticated-orcid":false,"given":"Ilias","family":"Bougoudis","sequence":"first","affiliation":[]},{"given":"Konstantinos","family":"Demertzis","sequence":"additional","affiliation":[]},{"given":"Lazaros","family":"Iliadis","sequence":"additional","affiliation":[]},{"given":"Vardis-Dimitris","family":"Anezakis","sequence":"additional","affiliation":[]},{"given":"Antonios","family":"Papaleonidas","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,6,24]]},"reference":[{"key":"3125_CR1","unstructured":"Education Research Centre of Greece. http:\/\/www.kee.gr\/perivallontiki\/teacher6_4.html . Accessed 1 Feb 2017"},{"key":"3125_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-319-11071-4_1","volume":"459","author":"I Bougoudis","year":"2014","unstructured":"Bougoudis I, Iliadis L, Papaleonidas A (2014) Fuzzy inference ANN ensembles for air pollutants modeling in a major urban area: the case of Athens. Eng Appl Neural Netw Commun Comput Inf Sci 459:1\u201314. doi: 10.1007\/978-3-319-11071-4_1","journal-title":"Eng Appl Neural Netw Commun Comput Inf Sci"},{"key":"3125_CR3","doi-asserted-by":"publisher","first-page":"424","DOI":"10.1007\/978-3-662-44654-6_42","volume":"436","author":"L Iliadis","year":"2014","unstructured":"Iliadis L, Bougoudis L, Spartalis S (2014) Comparison of self organizing maps clustering with supervised classification for air pollution data sets. Proc AIAI 436:424\u2013435. doi: 10.1007\/978-3-662-44654-6_42","journal-title":"Proc AIAI"},{"issue":"2","key":"3125_CR4","doi-asserted-by":"publisher","first-page":"115","DOI":"10.3233\/ICA-150505","volume":"23","author":"I Bougoudis","year":"2016","unstructured":"Bougoudis I, Demertzis K, Iliadis L (2016) Fast and low cost prediction of extreme air pollution values with hybrid unsupervised learning. Integr Comput Aided Eng 23(2):115\u2013127. doi: 10.3233\/ICA-150505","journal-title":"Integr Comput Aided Eng"},{"key":"3125_CR5","first-page":"51","volume":"629","author":"I Bougoudis","year":"2016","unstructured":"Bougoudis I, Demertzis K, Iliadis L, Anezakis VD, Papaleonidas A (2016) Semi-supervised hybrid modeling of atmospheric pollution in urban centers. Commun Comput Inf Sci 629:51\u201363","journal-title":"Commun Comput Inf Sci"},{"key":"3125_CR6","doi-asserted-by":"publisher","first-page":"1191","DOI":"10.1007\/s00521-015-1927-7","volume":"27","author":"I Bougoudis","year":"2016","unstructured":"Bougoudis I, Demertzis K, Iliadis L (2016) HISYCOL a hybrid computational intelligence system for combined machine learning: the case of air pollution modeling in Athens. EANN Neural Comput Appl 27:1191\u20131206. doi: 10.1007\/s00521-015-1927-7","journal-title":"EANN Neural Comput Appl"},{"key":"3125_CR7","doi-asserted-by":"publisher","unstructured":"Krithara A, Amini MR, Renders JM, Goutte C (2008) Semi-supervised document classification with a mislabeling error model. In: 30th European conference on IR research, ECIR 2008, advances in information retrieval, lecture notes in computer science, 4956:370\u2013381. doi: 10.1007\/978-3-540-78646-7_34","DOI":"10.1007\/978-3-540-78646-7_34"},{"key":"3125_CR8","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1016\/j.ins.2016.04.019","volume":"378","author":"RAR Ashfaq","year":"2017","unstructured":"Ashfaq RAR, Wang XZ, Huang JZ, Abbas H, He YL (2017) Fuzziness based semi-supervised learning approach for intrusion detection system. Inf Sci 378:484\u2013497. doi: 10.1016\/j.ins.2016.04.019","journal-title":"Inf Sci"},{"key":"3125_CR9","doi-asserted-by":"publisher","unstructured":"Yan Y, Chen L (2011) Label-based semi-supervised fuzzy co-clustering for document categoraization. In: 8th international conference on information, communications and signal processing, (ICICS) pp 1\u20135. doi: 10.1109\/ICICS.2011.6173605","DOI":"10.1109\/ICICS.2011.6173605"},{"key":"3125_CR10","doi-asserted-by":"publisher","unstructured":"Zheng A, Luo L (2012) A semi-supervised fuzzy SVM clustering framework. Recent advances in computer science and information engineering, lecture notes in electrical engineering, 1:525\u2013530. doi: 10.1007\/978-3-642-25781-0_78","DOI":"10.1007\/978-3-642-25781-0_78"},{"key":"3125_CR11","doi-asserted-by":"publisher","unstructured":"Le T, Tran D, Tran T, Nguyen K, Ma W (2013) Fuzzy entropy semi-supervised support vector data description. In: Proceedings of the international joint conference on neural networks, pp 1\u20135. doi: 10.1109\/IJCNN.2013.6707033","DOI":"10.1109\/IJCNN.2013.6707033"},{"key":"3125_CR12","doi-asserted-by":"publisher","DOI":"10.1109\/ISCID.2013.207","author":"Y Yan","year":"2013","unstructured":"Yan Y, Cui J, Pan Z (2013) Semi-supervised fuzzy relational classifier. Comput Intell Des ISCID. doi: 10.1109\/ISCID.2013.207","journal-title":"Comput Intell Des ISCID"},{"key":"3125_CR13","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1007\/978-3-642-23199-5_10","volume":"6871","author":"H Benbrahim","year":"2011","unstructured":"Benbrahim H (2011) Fuzzy Semi-supervised support vector machines. Mach Learn Data Min Pattern Recognit LNCS 6871:127\u2013139","journal-title":"Mach Learn Data Min Pattern Recognit LNCS"},{"key":"3125_CR14","doi-asserted-by":"publisher","unstructured":"El-Zahhar MM, El-Gayar NF (2010) A semi-supervised learning approach for soft labeled data. In: Proceedings of the 10th international conference on intelligent systems design and applications (ISDA) pp 1136\u20131141. doi: 10.1109\/ISDA.2010.5687034","DOI":"10.1109\/ISDA.2010.5687034"},{"key":"3125_CR15","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1016\/j.ins.2016.02.052","volume":"352\u2013353","author":"H Jamalabadi","year":"2016","unstructured":"Jamalabadi H, Nasrollahi H, Alizadeh S, Araabi BN, Ahamadabadi MN (2016) Competitive interaction reasoning: a bio-inspired reasoning method for fuzzy rule based classification systems. Inf Sci 352\u2013353:35\u201347. doi: 10.1016\/j.ins.2016.02.052","journal-title":"Inf Sci"},{"key":"3125_CR16","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1016\/j.eswa.2016.08.016","volume":"65","author":"FR Cordeiro","year":"2016","unstructured":"Cordeiro FR, Santos WP, Silva-Filho AG (2016) A semi-supervised fuzzy GrowCut algorithm to segment and classify regions of interest of mammographic images. Expert Syst Appl 65:116\u2013126","journal-title":"Expert Syst Appl"},{"key":"3125_CR17","doi-asserted-by":"publisher","unstructured":"Yan J, Qi W, Yue S, Zhang D, Guo D, Ma H (2016) Application of semi-supervised fuzzy kernel clustering algorithm in recognizing transformer winding\u2019s pressed state. In: ICSPCC 2016\u2014IEEE international conference on signal processing, communications and computing, conference proceedings, 7753697, Hong Kong, China, pp 1\u20136. doi: 10.1109\/ICSPCC.2016.7753697","DOI":"10.1109\/ICSPCC.2016.7753697"},{"key":"3125_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2016\/5206048","volume":"2016","author":"D Tanaka","year":"2016","unstructured":"Tanaka D, Honda K, Ubukata S, Notsu A (2016) A semi-supervised framework for MMMs-induced fuzzy co-clustering with virtual samples. Adv Fuzzy Syst 2016:1\u20138. doi: 10.1155\/2016\/5206048","journal-title":"Adv Fuzzy Syst"},{"key":"3125_CR19","doi-asserted-by":"publisher","unstructured":"Honda K, Ubukata S, Notsu A, Takahashi N, Ishikawa Y (2015) A semi-supervised fuzzy co-clustering framework and application to twitter data analysis. In: 4th international conference on informatics, electronics and vision, Fukuoka. pp 1\u20134. doi: 10.1109\/ICIEV.2015.7334057","DOI":"10.1109\/ICIEV.2015.7334057"},{"key":"3125_CR20","doi-asserted-by":"crossref","unstructured":"Jensen R, Vluymans S, Parthal\u00e1in NM, Cornelis C, Saeys Y (2015) Semi-supervised fuzzy-rough feature selection. Lecture notes in computer science including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics 9437:185\u2013195","DOI":"10.1007\/978-3-319-25783-9_17"},{"key":"3125_CR21","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1007\/978-3-319-14633-1_5","volume":"341","author":"T Le","year":"2015","unstructured":"Le T, Nguyen V, Pham T, Dinh M, Le TH (2015) Fuzzy semi-supervised large margin one-class support vector machine. Adv Intell Syst Comput 341:65\u201378","journal-title":"Adv Intell Syst Comput"},{"issue":"4","key":"3125_CR22","doi-asserted-by":"crossref","first-page":"992","DOI":"10.1109\/TFUZZ.2015.2466085","volume":"24","author":"I Diaz-Valenzuela","year":"2016","unstructured":"Diaz-Valenzuela I, Vila MA, Martin-Bautista MJ (2016) On the use of fuzzy constraints in semisupervised clustering. IEEE Trans Fuzzy Syst 24(4):992\u2013999","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"3","key":"3125_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1142\/S0218213013500139","volume":"22","author":"O Bchir","year":"2013","unstructured":"Bchir O, Frigui H, Ismail MMB (2013) Semi-supervised fuzzy clustering with learnable cluster dependent kernels. Int J Artif Intell Tools 22(3):1\u201326. doi: 10.1142\/S0218213013500139","journal-title":"Int J Artif Intell Tools"},{"issue":"3","key":"3125_CR24","first-page":"93","volume":"29","author":"P Sen","year":"2008","unstructured":"Sen P, Namata G, Bilgic M, Getoor L, Galligher B, Eliassi-Rad T (2008) Collective classification in network data. Adv Artif Int 29(3):93\u2013106","journal-title":"Adv Artif Int"},{"key":"3125_CR25","isbn-type":"print","volume-title":"Learning and soft computing","author":"V Kecman","year":"2001","unstructured":"Kecman V (2001) Learning and soft computing. MIR Press, Moscow. ISBN 9780262112550","ISBN":"https:\/\/id.crossref.org\/isbn\/9780262112550"},{"key":"3125_CR26","unstructured":"Iliadis L (2007) Intelligent information systems and application in risk estimation. Stamoulis Publishing, Thessaloniki"},{"key":"3125_CR27","unstructured":"Iliadis L, Papaleonidas A (2016) Computational intelligence an intelligent agents. Tziolas publications, Thessaloniki"},{"key":"3125_CR28","volume-title":"Fuzzy modeling and genetic algorithms for data mining and exploration","author":"E Cox","year":"2005","unstructured":"Cox E (2005) Fuzzy modeling and genetic algorithms for data mining and exploration. Elsevier Science, USA"},{"key":"3125_CR29","doi-asserted-by":"publisher","unstructured":"Anezakis VD, Dermetzis K, Iliadis L, Spartalis S (2016) Fuzzy cognitive maps for long-term prognosis of the evolution of atmospheric pollution, based on climate change scenarios: The case of Athens. Lecture notes in computer science (lecture notes in artificial intelligence and lecture notes in bioinformatics) 9875:175\u2013186. doi: 10.1007\/978-3-319-45243-2_16","DOI":"10.1007\/978-3-319-45243-2_16"},{"key":"3125_CR30","first-page":"63","volume-title":"Facets of uncertainties and applications, ICFUA","author":"P Ghosh","year":"2013","unstructured":"Ghosh P, Kundu K (2013) Photo-fuzzy concepts generation technique using fuzzy graph. In: Chakraborty MK, Skowron A, Maiti M, Kar S (eds) Facets of uncertainties and applications, ICFUA. Springer, Kolkata, pp 63\u201372"},{"key":"3125_CR31","series-title":"Advances in fuzzy systems-applications and theory","doi-asserted-by":"crossref","DOI":"10.1142\/4177","volume-title":"Genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases","author":"O Cordon","year":"2001","unstructured":"Cordon O, Herrera F, Hoffmann F, Magdalena L (2001) Genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. Advances in fuzzy systems-applications and theory, vol 19. World Scientific Publishing, Hong Kong"},{"key":"3125_CR32","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1080\/00031305.1994.10476030","volume":"48","author":"F Pukelsheim","year":"1994","unstructured":"Pukelsheim F (1994) The three sigma rule. Am Stat 48:88\u201391","journal-title":"Am Stat"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-017-3125-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-017-3125-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-017-3125-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,24]],"date-time":"2024-06-24T23:46:09Z","timestamp":1719272769000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-017-3125-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,6,24]]},"references-count":32,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2018,4]]}},"alternative-id":["3125"],"URL":"https:\/\/doi.org\/10.1007\/s00521-017-3125-2","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2017,6,24]]}}}