Data Analytics in System Engineering

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Geliefert zwischen Mi., 25.02.2026 und Do., 26.02.2026

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These proceedings offer an insightful exploration of integrating data analytics in system engineering. This book highlights the essential role of data in driving innovation, optimizing processes, and solving complex challenges in the field. Targeted at industry professionals, researchers, and enthusiasts, this book serves as a comprehensive resource, providing actionable insights and showcasing transformative applications of data in engineering. It is a must-read for anyone keen on understanding and participating in the ongoing evolution of system engineering in our data-centric world.

Presents the latest research on Software Engineering Application in Informatics Gathers the Proceedings of the 7th Computational Methods in Systems and Software 2023 (CoMeSySo2023) conference Written by experts in the field

Inhalt
Interpretable Rules with a Simplified Data Representation - a Case Study with the EMBER dataset.- Spatial econometric models: the pursuit of an accurate spatial structure with an application to labor market.- Use of Neighborhood-based Bridge Node Centrality Tuple for Preferential Vaccination of Nodes to Reduce the Number of Infected Nodes in a Complex Real-World Network.- Social Media Applications' Privacy Policies for facilitating Digital Living.- Modeling the Alienability of an Electronic Document.- Particular Analysis of Regression Effect Sizes Applied on Big Data Set.- Foreign Languages Teaching Technologies and Methods in Traditional and Distance Forms of Learning.- Application of Fuzzy Logic for Evaluating Student Learning Outcomes in E-Learning.- The meaning of business and software architecture in the enterprise architecture.- Research of the Correlation Between the Results of Detection the Liveliness of a Face and its Identification by Facial Recognition Systems.- Profit Prediction Model for Steel Enterprises Based on Input and Output Prices.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783031548192
    • Genre Technology Encyclopedias
    • Editor Radek Silhavy, Petr Silhavy
    • Lesemotiv Verstehen
    • Anzahl Seiten 556
    • Herausgeber Springer
    • Größe H235mm x B155mm x T30mm
    • Jahr 2024
    • EAN 9783031548192
    • Format Kartonierter Einband
    • ISBN 3031548191
    • Veröffentlichung 24.02.2024
    • Titel Data Analytics in System Engineering
    • Untertitel Proceedings of 7th Computational Methods in Systems and Software 2023, Vol. 4
    • Gewicht 832g
    • Sprache Englisch

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