Proceedings of the 15th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2023) : Volume 4: Real World Applications / edited by Anu Bajaj, Ajith Abraham, K. Reddy Madhavi, Oscar Castillo

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Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Lecture Notes in Networks and Systems ; 1247Verlag: Cham : Springer Nature Switzerland, 2025Verlag: Cham : Imprint: Springer, 2025Auflage: 1st ed. 2025Beschreibung: 1 Online-Ressource(XVIII, 527 p. 237 illus., 186 illus. in color.)ISBN:

9783031810862

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Andere physische Formen: 9783031810855 | 9783031810879 | Erscheint auch als: 9783031810855 Druck-Ausgabe | Erscheint auch als: 9783031810879 Druck-AusgabeDDC-Klassifikation:

006.3 23

DOI: DOI: 10.1007/978-3-031-81086-2Online-Ressourcen:

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Zusammenfassung: An evolutionary framework for different variants of the fair layout optimization problem -- The Use of AI in Pharma: Results from mapping of Peer-reviewed and Grey literature across the world -- Enhanced Approach for Precision Agriculture using AI/ML Techniques -- Particle Swarm Optimization based on Novelty Search -- Gold Rate Historical Data Analysis -- Classification of teas using Machine and Deep Learning methods on a custom e-nose platform -- Utilization of Machine Learning Algorithms to Monitor the Growth Path of Fishes in Marine Aquaculture.Zusammenfassung: This book presents 57 selected papers focused on Real World Applications from the 14th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2023) and 14th World Congress on Nature and Biologically Inspired Computing (NaBIC 2023). SoCPaR – NaBIC 2023 was held in 5 different cities namely Olten, Switzerland; Porto, Portugal; Kaunas, Lithuania; Greater Noida, India; Kochi, India and in online mode. The conference had contributions by authors from 39 countries. This Volume comprising of 57 articles offers a valuable reference guide for all scientists, academicians, researchers, students and practitioners focused on real-world applications of soft computing and nature inspired methodologies.PPN: PPN: 1925485579Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-INR | ZDB-2-SXIT

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