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020 _a9783031379598
_9978-3-031-37959-8
024 7 _a10.1007/978-3-031-37959-8
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
100 1 _aKóczy, László T.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_968284
245 1 0 _aFuzzy Cognitive Maps
_h[electronic resource] :
_bA Tool for the Modeling and Simulation of Processes and Systems /
_cby László T. Kóczy.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXVII, 133 p. 33 illus., 6 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Fuzziness and Soft Computing,
_x1860-0808 ;
_v427
505 0 _aIntroduction to Fuzzy Cognitive Maps -- Systemic Relationships Between Regional Sustainability and Waste Management -- Identification of the Main Factors (Concepts) of Waste Management for Building the Initial FCM Model -- Rethinking the Set of Concepts - Applying Expert Analysis by the Workshop Method -- Model Reduction Methods -- Text Mining Based on the Literature of Waste Management as the Source of a Reconstructed Time Series -- Behavioral Analysis of Fuzzy Cognitive Maps -- Fuzzy Cognitive Maps: Mathematical Challenges -- Dynamics of Classical Fuzzy Cognitive Maps -- Dynamics of Fuzzy Cognitive Maps with Uncertain Weights.
520 _aThis book is considered as a monograph but also as a potential textbook for graduate students, focusing on the application of FCMs for modelling and analysing the behaviour of multicomponent systems. In the last two decades, no monograph or textbook has been published on the topic Fuzzy Cognitive Maps (FCM), so this new book is definitely filling a gap in the literature of computational intelligence. The book is built up didactically, the novel results in the field being presented in the way of starting with two real-life case studies, one in the area of waste management, while the other one in modelling bank management systems. In both cases, the book starts with explaining the applied problem and then presenting how the model construction is done and what problems emerge when attempts are made for applying directly earlier results on FCM modelling. In the first case study, the problem of the oversimplification leads to inadequacy of the model, and then it is shown how new, much finer models can be built up based on expert domain knowledge. Then, the new problem of losing transparency and interpretability emerges, and as a solution, a new algorithm family is proposed that reduces FCMs to fewer components, while preserving the essential characteristics of the original model. The second case study raises the problems of stability and sensitivity of FCMs, especially, considering that expert knowledge is often uncertain and subjective. The new results summarised in the book target the questions of how to ascertain whether an FCM is converging to one or several fixed point attractors, whether there is a bifurcation when parameters are changing, etc. Both problems deal with the ultimate question whether the system modelled is stable and sustainable.<.
650 0 _aComputational intelligence.
_964052
650 0 _aArtificial intelligence.
_958441
650 1 4 _aComputational Intelligence.
_964052
650 2 4 _aArtificial Intelligence.
_958441
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031379581
776 0 8 _iPrinted edition:
_z9783031379604
776 0 8 _iPrinted edition:
_z9783031379611
830 0 _aStudies in Fuzziness and Soft Computing,
_x1860-0808 ;
_v427
_968285
856 4 0 _uhttps://doi.org/10.1007/978-3-031-37959-8
912 _aZDB-2-INR
912 _aZDB-2-SXIT
999 _c56829
_d56829