Fuzzy Cognitive Maps (eBook)

Best Practices and Modern Methods
eBook Download: PDF
2024 | 1st ed. 2024
XIII, 219 Seiten
Springer Nature Switzerland (Verlag)
978-3-031-48963-1 (ISBN)

Lese- und Medienproben

Fuzzy Cognitive Maps -
Systemvoraussetzungen
139,09 inkl. MwSt
  • Download sofort lieferbar
  • Zahlungsarten anzeigen

This book starts with the rationale for creating an FCM by contrast to other techniques for participatory modeling, as this rationale is a key element to justify the adoption of techniques in a research paper. Fuzzy cognitive mapping is an active research field with over 20,000 publications devoted to externalizing the qualitative perspectives or 'mental models' of individuals and groups. Since the emergence of fuzzy cognitive maps (FCMs) back in the 80s, new algorithms have been developed to reduce bias, facilitate the externalization process, or efficiently utilize quantitative data via machine learning. It covers the development of an FCM with participants through a traditional in-person setting, drawing from the experience of practitioners and highlighting solutions to commonly encountered challenges. The book continues with introducing principles of simulations with FCMs as a tool to perform what-if scenario analysis, while extending those principles to more elaborated simulation scenarios where FCMs and agent-based modeling are combined. Once an FCM model is obtained, the book then details the analytical tools available for practitioners (e.g., to identify the most important factors) and provides examples to aid in the interpretation of results. The discussion concerning relevant extensions is equally pertinent, which are devoted to increasing the expressiveness of the FCM formalism in problems involving uncertainty. The last four chapters focus on building FCM models from historical data. These models are typically needed when facing multi-output prediction or pattern classification problems. In that regard, the book smoothly guides the reader from simple approaches to more elaborated algorithms, symbolizing the noticeable progress of this field in the last 35 years. Problems, recent references, and functional codes are included in each chapter to provide practice and support further learning from practitioners and researchers.



?Dr. Philippe J. Giabbanelli received his B.S. from Université Côte d'Azur (France) and his M.Sc. and Ph.D. from Simon Fraser University (Canada). He worked as a researcher at the University of Cambridge (UK) and as a tenure-track faculty at several nationally ranked American universities, where he developed a variety of courses on predictive modeling and artificial intelligence. He taught fuzzy cognitive maps (FCMs) from the perspective of AI, as an object of study for network science, or as a tool in modeling and simulation. His research focuses on developing and applying AI to support population health interventions. He has published about 130 articles (mostly with his students), covering multiple aspects of FCM research from the elicitation and aggregation of causal maps to their structural validation or their combination with other techniques such as agent-based modeling.
 

Dr. Gonzalo Nápoles received his B.S. and M.Sc. from the Central University of Las Villas (Cuba) and his Ph.D. from Hasselt University (Belgium) and Maastricht University (the Netherlands). Currently, he is a tenured assistant professor at the Department of Cognitive Science and Artificial Intelligence, Tilburg University (the Netherlands). He has taught fuzzy cognitive maps (FCMs) in several courses, including the First Summer School on Fuzzy Cognitive Mapping held in Volos (Greece). His research focuses on developing learning algorithms for FCM models, understanding their mathematical properties, and exploiting their potentialities in pattern classification and time series forecasting settings. He was a recipient of the Cuban Academy of Science Award for his contributions to the FCM field. More recently, his research efforts have shifted toward developing fair machine learning algorithms that can intrinsically be explained (to a large extent) and methods to mitigate implicit and explicit bias.
Erscheint lt. Verlag 29.1.2024
Zusatzinfo XIII, 219 p. 57 illus., 55 illus. in color.
Sprache englisch
Themenwelt Mathematik / Informatik Informatik
Mathematik / Informatik Mathematik
Technik Bauwesen
Wirtschaft Betriebswirtschaft / Management Wirtschaftsinformatik
Schlagworte cognitive networks • Fuzzy cognitive maps • Granular Computing • Graphical model • Interpretable Neural Models • Map-Based Reasoning Model • mental models • multi-attribute decision-making • participatory modeling • Recurrent Neural Networks
ISBN-10 3-031-48963-2 / 3031489632
ISBN-13 978-3-031-48963-1 / 9783031489631
Haben Sie eine Frage zum Produkt?
PDFPDF (Wasserzeichen)
Größe: 6,8 MB

DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasser­zeichen und ist damit für Sie persona­lisiert. Bei einer missbräuch­lichen Weiter­gabe des eBooks an Dritte ist eine Rück­ver­folgung an die Quelle möglich.

Dateiformat: PDF (Portable Document Format)
Mit einem festen Seiten­layout eignet sich die PDF besonders für Fach­bücher mit Spalten, Tabellen und Abbild­ungen. Eine PDF kann auf fast allen Geräten ange­zeigt werden, ist aber für kleine Displays (Smart­phone, eReader) nur einge­schränkt geeignet.

Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.

Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.

Mehr entdecken
aus dem Bereich
Datenanalyse für Künstliche Intelligenz

von Jürgen Cleve; Uwe Lämmel

eBook Download (2024)
De Gruyter (Verlag)
74,95
Digitale Geschäftsmodelle auf Basis Künstlicher Intelligenz

von Christian Aichele; Jörg Herrmann

eBook Download (2023)
Springer Fachmedien Wiesbaden (Verlag)
54,99
Wie Sie Daten für die Steuerung von Unternehmen nutzen

von Mischa Seiter

eBook Download (2023)
Vahlen (Verlag)
39,99