Computer aided systems theory - EURO...
International Conference on Computer Aided Systems Theory (2024 :)

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  • Computer aided systems theory - EUROCAST 2024 = 19th International Conference, Las Palmas de Gran Canaria, Spain, February 25 - March 1, 2024 : revised selected papers.. Part I /
  • Record Type: Electronic resources : Monograph/item
    Title/Author: Computer aided systems theory - EUROCAST 2024/ edited by Alexis Quesada-Arencibia, Michael Affenzeller, Roberto Moreno-Díaz.
    Reminder of title: 19th International Conference, Las Palmas de Gran Canaria, Spain, February 25 - March 1, 2024 : revised selected papers.
    remainder title: EUROCAST 2024
    other author: Quesada-Arencibia, Alexis.
    corporate name: International Conference on Computer Aided Systems Theory
    Published: Cham :Springer Nature Switzerland : : 2025.,
    Description: xxiv, 462 p. :ill. (some col.), digital ;24 cm.
    [NT 15003449]: Systems Theory, Applications, Pioneers, and Landmarks. -- The Application of Named Entity Recognition in Military Intelligence. -- A System-Theoretical Multi-Agent Approach to Human Computer Interaction. -- Data Transformation: Limitless Strategies in Energy Consumption. -- Theory and Applications of Metaheuristic Algorithms. -- VFLBench: A Practical Benchmark for Vertical Federated Learning in Smart Manufacturing. -- A Hybrid Cooperative Approach for Symbolic Regression. -- Comparing Constraint Evaluation Methods for Shape constrained Regression. -- Re-evaluation in Dynamic Tree-Search with Backtracking from Known Solutions. -- Application of Adapt-CMSA to the Electric Vehicle Routing Problem with Simultaneous Pickup and Deliveries. -- Optimizing Public Transport Through Integration of Microscopic and Macroscopic Simulations. -- Automated Inference of Domain Knowledge in Scientific Machine Learning. -- Automated Guided Vehicles in Yard Logistics: A time dependent approach. -- Diversity Management in Evolutionary Dynamic Optimization. -- Tackling the α-Domination Problem Heuristically. -- A Comparison of Recent Algorithms for Symbolic Regression to Genetic Programming. -- Composable Evolutionary Computation. -- Solving the Manhattan Metric Straddle Carrier Routing Problem with Buffer Areas using a Hybrid Metaheuristic Method. -- Route Planning for Parcel Logistics Systems with Reusable Packaging. -- Selecting User Queries in Interactive Job Scheduling. -- Improvements in Large Neighborhood Search for the Electric Autonomous Dial-A-Ride Problem. -- A Hybrid Metaheuristic for a Tourist Route Recommender. -- Learning to Select Promising Initial Solutions for Large Neighborhood Search-Based Multi-Agent Path Finding. -- A Learning Twolevel Optimization Approach for the Demand Maximizing Battery Swapping Station Location Problem. -- Learning Value Functions for Same-Day Delivery Problems in the Tardiness Regime. -- Vectorial Genetic Programming - Optimizing Segments for Feature Extraction. -- Mechatronic Product Development. -- Enhancing Manufacturing Efficiency through Integration of MBSE and Capella in the Digital Thread. -- Leveraging Learning Factories for Mechatronic Systems Development: A Collaborative Approach. -- CNN Based Radar Kick Sensor Gesture Recognition Prototype. -- Comparison of Different Battery-powered Tag Positions for Lower Limb Gesture Detection. -- Model-Based System Design, Verification and Simulation. -- Comparison of Physiological Data Acquisition for Modeling of drivers in Autonomous Vehicles. -- Automated control of robots via 5G communication from Multi Accesss Edge Computing. -- Automatic classification of cow's behavior during grazing. -- Programming Learning through the Use of ChatGPT. -- ChatGTP Language Model as Support for Teaching and Self learning in the Field of Engineering and Technical Sciences. -- Analytical Conversion of the Strejc Model to the First Order with Time Delay (FOTD) Model. -- Neural Analysis of Parameters Occurring in a Smart Building. -- Efficient Manipulation of Control Flow Models in Evolving Software. -- Textile Sensor Surrogate Modelling using Sparse Identification. -- Discrimination Criteria for Modeling Association, Aggregation, and Composition in UML Class Diagrams.
    Contained By: Springer Nature eBook
    Subject: Computer-aided engineering - Congresses. -
    Online resource: https://doi.org/10.1007/978-3-031-82949-9
    ISBN: 9783031829499
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