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Advances in Computational Intelligence Systems: Contributions Presented at the 20th UK Workshop on Computational Intelligence, September 8-10, 2021, Aberystwyth, Wales, UK 1st ed. 2022 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 579 pages, height x width: 235x155 mm, weight: 896 g, 207 Illustrations, color; 50 Illustrations, black and white; XI, 579 p. 257 illus., 207 illus. in color., 1 Paperback / softback
  • Sērija : Advances in Intelligent Systems and Computing 1409
  • Izdošanas datums: 18-Nov-2021
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030870936
  • ISBN-13: 9783030870935
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Advances in Computational Intelligence Systems: Contributions Presented at the 20th UK Workshop on Computational Intelligence, September 8-10, 2021, Aberystwyth, Wales, UK 1st ed. 2022Palielināt
  • Formāts: Paperback / softback, 579 pages, height x width: 235x155 mm, weight: 896 g, 207 Illustrations, color; 50 Illustrations, black and white; XI, 579 p. 257 illus., 207 illus. in color., 1 Paperback / softback
  • Sērija : Advances in Intelligent Systems and Computing 1409
  • Izdošanas datums: 18-Nov-2021
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030870936
  • ISBN-13: 9783030870935
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783030870935.html
This book contains the papers presented at the 20th UK Workshop on Computational Intelligence (UKCI 2021), held virtually by Aberystwyth University, 8–10th September 2021. This marks the 20th anniversary of UKCI; a testament to the increasing role and importance of Computational Intelligence (CI) and the continuing interest in its development. UKCI provides a forum for the academic community and industry to share ideas and experience in this field. EDMA 2021, the 4th International Engineering Data- and Model-Driven Applications workshop, is also incorporated and held in conjunction with UKCI 2021. Paper submissions were invited in the areas of fuzzy systems, neural networks, evolutionary computation, machine learning, data mining, cognitive computing, intelligent robotics, hybrid methods, deep learning and applications of CI.
An Evolving Feature Weighting Framework for Granular Fuzzy Logic Models.- Fuzzy Multi-Criteria Decision-Making: Example of an explainable classification framework.- Rough-Fuzzy Rule Interpolation for Data-Driven Decision Making.- Fuzzy Intelligent System for Improving High Availability of a Docker-Based Hybrid Cloud Infrastructure.- A Study of Neuro-weighted Nearest-neighbour Classification.- Q-Routing with Multiple Soft Requirements.- Avoiding Excess Computation in Asynchronous Evolutionary Algorithms.- Stochasticity improves evolvability in articial gene regulatory networks.- ACO Inspired GA Mutation Applied to the TSP.- Centralised and Decentralised Control of Video Game Agents.