Data Analytics in System Engineering [electronic resource] : Proceedings of 7th Computational Methods in Systems and Software 2023, Vol. 4 / edited by Radek Silhavy, Petr Silhavy.
Material type:
TextSeries: Lecture Notes in Networks and Systems ; 935Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edition: 1st ed. 2024Description: XV, 537 p. 236 illus., 200 illus. in color. online resourceContent type: - text
- computer
- online resource
- 9783031548208
- Q342
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.
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.
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