UID:
almahu_9948612940502882
Format:
XXVII, 876 p. 371 illus., 267 illus. in color.
,
online resource.
Edition:
1st ed. 2021.
ISBN:
9783030578022
Series Statement:
Advances in Intelligent Systems and Computing, 1268
Content:
This book contains accepted papers presented at SOCO 2020 conference held in the beautiful and historic city of Burgos (Spain), in September 2020. Soft computing represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. After a through peer-review process, the SOCO 2020 International Program Committee selected 83 papers which are published in these conference proceedings and represents an acceptance rate of 35%. Due to the COVID-19 outbreak, the SOCO 2020 edition was blended, combining on-site and on-line participation. In this relevant edition a special emphasis was put on the organization of special sessions. Eleven special session were organized related to relevant topics such as: Soft Computing Applications in Precision Agriculture, Manufacturing and Management Systems, Management of Industrial and Environmental Enterprises, Logistics and Transportation Systems, Robotics and Autonomous Vehicles, Computer Vision, Laser-Based Sensing and Measurement and other topics such as Forecasting Industrial Time Series, IoT, Big Data and Cyber Physical Systems, Non-linear Dynamical Systems and Fluid Dynamics, Modeling and Control systems The selection of papers was extremely rigorous in order to maintain the high quality of SOCO conference editions and we would like to thank the members of the Program Committees for their hard work in the reviewing process. This is a crucial process to the creation of a high standard conference and the SOCO conference would not exist without their help.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783030578015
Additional Edition:
Printed edition: ISBN 9783030578039
Language:
English
DOI:
10.1007/978-3-030-57802-2
URL:
https://doi.org/10.1007/978-3-030-57802-2
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