Data Analytics and Computational Intelligence: Novel Models, Algorithms and Applications -

Data Analytics and Computational Intelligence: Novel Models, Algorithms and Applications

Buch | Softcover
IX, 605 Seiten
2024 | 2023
Springer International Publishing (Verlag)
978-3-031-38327-4 (ISBN)
235,39 inkl. MwSt

In the age of transformative artificial intelligence (AI), which has the potential to revolutionize our lives, this book provides a comprehensive exploration of successful research and applications in AI and data analytics.

Covering innovative approaches, advanced algorithms, and data analysis methodologies, this book addresses complex problems across topics such as machine learning, pattern recognition, data mining, optimization, and predictive modeling.

With clear explanations, practical examples, and cutting-edge research, this book seeks to expand the understanding of a wide readership, including students, researchers, practitioners, and technology enthusiasts eager to explore these exciting fields.

Featuring real-world applications in education, health care, climate modeling, cybersecurity, smart transportation, conversational systems, and material analysis, among others, this book highlights how these technologies can drive innovation and generate competitive advantages.


Cluster Analysis using k-means in school dropout.- Topic modeling based on OWA aggregation to improve the semantic focusing on relevant information extraction problems.- An Affiliated Approach to Data Validation: The US 2020 Governor's County Election.- Acquisition, Processing and Visualization of Meteorological Data in Real-Time using Apache Flink.- Topological Data Analysis for the evolution of student grades before, during and after the COVID-19 pandemic.- Redescending M-Estimators analysis on the Intuitionistic Fuzzy clustering algorithm for skin lesion delimitation.- Big Data Platform as a Service for Anomaly Detection.- An overview of model-driven and data-driven forecasting methods for smart transportation.- Data augmentation techniques for facial image generation: a brief literature review.- A review on machine learning-aided multi-omics data integration techniques for healthcare.- Learning of Conversational Systems based on Linguistic Data Summarization applicationsin BIM environments.- Fuzzified case-based reasoning blockchain framework for predictive maintenance in Industry 4.0.- Machine learning for identifying atomic species from optical emission spectra generated by an atmospheric pressure non-thermal plasma.- Agent-based simulation: various scenarios.- Multi-Hop Ridesharing NPC.- A content-based group recommender system using feature weighting and virtual users aggregation.- Performance Evaluation of AquaFeL-PSO Informative Path Planner under Different Contamination Profiles.- Adapting Swarm Intelligence to a Fixed Wing Unmanned Combat Aerial Vehicle Platform.- Cellular Processing Algorithm for Time Dependent-Traveling Salesman Problem.- Portfolio Optimization using Reinforcement Learning and Hierarchical Risk Parity Approach.- Reducing recursion costs in last-mile delivery routes with failed deliveries.- Intelligent Decision-Making Dashboard for CNC Milling Machines in Industrial Equipment: A Comparative Analysis of MOORA and TOPSIS Methods

Erscheinungsdatum
Reihe/Serie Studies in Big Data
Zusatzinfo IX, 605 p. 296 illus., 244 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Themenwelt Mathematik / Informatik Informatik Datenbanken
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Technik
Schlagworte Augmented Analytics • Big Data Environments • Case Studies and Applications • data-driven decisions • Data Visualization • Data Warehousing • Forecasting Methods • Fuzzy Sets and Fuzzy Logic • Knowledge Discovery • Knowledge Representation • Metaheuristic Algorithms • multi-criteria decision making • Natural Language Processing • operational performance • Recommender Systems • Single and Multi-objective Optimization • Statistical Data Analysis • supervised learning algorithms • text analytics • Unsupervised Learning Algorithms
ISBN-10 3-031-38327-3 / 3031383273
ISBN-13 978-3-031-38327-4 / 9783031383274
Zustand Neuware
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