Applications of Soft Computing in Time Series Forecasting: Simulation and Modeling Techniques (Studies in Fuzziness and Soft Computing, Band 330) - Softcover

Singh, Pritpal

Softcover

ISBN 10: 331938726X ISBN 13: 9783319387260

Verlag: Springer, 2016

Inhaltsangabe

This book reports on an in-depth study of fuzzy time series (FTS) modeling. It reviews and summarizes previous research work in FTS modeling and also provides a brief introduction to other soft-computing techniques, such as artificial neural networks (ANNs), rough sets (RS) and evolutionary computing (EC), focusing on how these techniques can be integrated into different phases of the FTS modeling approach. In particular, the book describes novel methods resulting from the hybridization of FTS modeling approaches with neural networks and particle swarm optimization. It also demonstrates how a new ANN-based model can be successfully applied in the context of predicting Indian summer monsoon rainfall. Thanks to its easy-to-read style and the clear explanations of the models, the book can be used as a concise yet comprehensive reference guide to fuzzy time series modeling, and will be valuable not only for graduate students, but also for researchers and professionals working for academic, business and government organizations.

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Über die Autorin bzw. den Autor

PRITPAL SINGH, assistant professor in Central University of Rajasthan, India. He has an academic experience of more than 7 years. He served as a Senior Postdoctoral Fellow in the Department of Electrical Engineering at the Taipei National University of Technology, Taiwan, from 2019-2020. He is working as an Adjunct Professor (Research) from November, 2020 in the Institute of Theoretical Physics, Jagiellonian University, Poland. He is an active research member of Bio-Data Research Group (under TEAM-NET Program) in the Institute of Theoretical Physics, Jagiellonian University. His research interests include ambiguous set theory, soft computing, optimization algorithms (especially quantum-based optimization), time series forecasting, image analysis, fMRI data analysis, machine learning, mathematical modeling and simulation. He has published numerous papers in refereed SCI journals, conference proceedings, book chapters and book.

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This book reports on an in-depth study of fuzzy time series (FTS) modeling. It reviews and summarizes previous research work in FTS modeling and also provides a brief introduction to other soft-computing techniques, such as artificial neural networks (ANNs), rough sets (RS) and evolutionary computing (EC), focusing on how these techniques can be integrated into different phases of the FTS modeling approach. In particular, the book describes novel methods resulting from the hybridization of FTS modeling approaches with neural networks and particle swarm optimization. It also demonstrates how a new ANN-based model can be successfully applied in the context of predicting Indian summer monsoon rainfall. Thanks to its easy-to-read style and the clear explanations of the models, the book can be used as a concise yet comprehensive reference guide to fuzzy time series modeling, and will be valuable not only for graduate students, but also for researchers and professionals working for academic, business and government organizations.

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2016
• Sprache: Englisch
• ISBN 10: 331938726X
• ISBN 13: 9783319387260
• Einband: Taschenbuch
• Anzahl der Seiten: 180
• Kontakt zum Hersteller: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Deutschland