Overview
- Presents a novel framework for using soft computing for future studies
- Describes a set of methods aimed at reducing uncertainty, thus improving the inference process
- Offers strategies to merge qualitative and quantitative approaches into prospective studies
Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 387)
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Table of contents (8 chapters)
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Front Matter
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Approaches to Futures Studies
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Front Matter
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Meta-Prospective: An Enhanced Approach for Strategic Prospective
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Front Matter
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Towards a Cloud-Based Adaptive Learning Environment
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Front Matter
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Back Matter
Keywords
- Fuzzy Optimization Models
- Fuzzy Decision Making
- Extended Prospective Model
- Fuzzy Reasoning
- Fuzzy Inference
- Strategic Planning with Fuzzy Logic
- Hybrid Fuzzy Modeling
- Cloud-Based Adaptive Learning
- Scenario Building
- Strategic Fitting Process
- Future Lighthouse Trend Scenarios (Flights)
- Fuzzy MCDM
- Fuzzy Cognitive Maps
- Corporate Foresight with Fuzzy Methods
- Strategic Prospective with Fuzzy Methods
- Meta-Prospective
About this book
This book discusses how to build optimization tools able to generate better future studies. It aims at showing how these tools can be used to develop an adaptive learning environment that can be used for decision making in the presence of uncertainties. The book starts with existing fuzzy techniques and multicriteria decision making approaches and shows how to combine them in more effective tools to model future events and take therefore better decisions. The first part of the book is dedicated to the theories behind fuzzy optimization and fuzzy cognitive map, while the second part presents new approaches developed by the authors with their practical application to trend impact analysis, scenario planning and strategic formulation. The book is aimed at two groups of readers, interested in linking the future studies with artificial intelligence. The first group includes social scientists seeking for improved methods for strategic prospective. The second group includes computer scientists and engineers seeking for new applications and current developments of Soft Computing methods for forecasting in social science, but not limited to this.
Authors and Affiliations
Bibliographic Information
Book Title: Integrating Soft Computing into Strategic Prospective Methods
Book Subtitle: Towards an Adaptive Learning Environment Supported by Futures Studies
Authors: Raúl Trujillo-Cabezas, José Luis Verdegay
Series Title: Studies in Fuzziness and Soft Computing
DOI: https://doi.org/10.1007/978-3-030-25432-2
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-25431-5Published: 06 September 2019
Softcover ISBN: 978-3-030-25434-6Published: 06 September 2020
eBook ISBN: 978-3-030-25432-2Published: 28 August 2019
Series ISSN: 1434-9922
Series E-ISSN: 1860-0808
Edition Number: 1
Number of Pages: XXII, 230
Topics: Computational Intelligence, Operations Research, Management Science, Artificial Intelligence, Operations Research/Decision Theory