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J. Fuzzy Syst."],"published-print":{"date-parts":[[2023,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Fuzzy cognitive networks (FCNs) arose from traditional fuzzy cognitive maps (FCMs) to have the advantage of guaranteed convergence to equilibrium points, thus being more suitable than conventional FCMs for a variety of pattern recognition and system identification tasks. Moreover, recent developments led to FCNs with functional weights (FCNs-FW), as a significant FCNs enhancement in terms of storage requirements, efficiency and less human intervention requirements. In this paper we proceed further by introducing hybrid deep learning structures, interweaving FCNs-FW with well established deep neural network (DNN) representative structures and apply the new schemes on a variety of pattern recognition and time series prediction tasks. More specifically, after discussing general issues related to the construction of deep learning structures using FCNs-FW we present three hybrid models, which combine the FCN-FW with convolutional neural networks (CNNs), echo state networks (ESNs) and AutoEncoder (AE) schemes, respectively. The hybrid schemes are tested on diverse benchmark data sets and prove that FCN-FW based hybrid schemes perform equally well or better than state-of-the-art DNN-based schemes, paving thus the way for using cognitive networks to deep learning representative structures.<\/jats:p>","DOI":"10.1007\/s40815-023-01564-4","type":"journal-article","created":{"date-parts":[[2023,7,10]],"date-time":"2023-07-10T15:02:35Z","timestamp":1689001355000},"page":"2534-2554","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Fuzzy Cognitive Networks in Diverse Applications Using Hybrid Representative Structures"],"prefix":"10.1007","volume":"25","author":[{"given":"Georgios D.","family":"Karatzinis","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nikolaos A.","family":"Apostolikas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiannis S.","family":"Boutalis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"George A.","family":"Papakostas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,7,10]]},"reference":[{"issue":"1","key":"1564_CR1","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/S0020-7373(86)80040-2","volume":"24","author":"B Kosko","year":"1986","unstructured":"Kosko, B., et al.: Fuzzy cognitive maps. 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