Artificial Intelligence, Data Science and Applications (eBook, PDF)

ICAISE'2023, Volume 1
Redaktion: Farhaoui, Yousef; Verma, Anshul; Taherdoost, Hamed; Saba, Tanzila; Hussain, Amir

• Format: PDF

Produktbeschreibung

¿This book is to provide a comprehensive reference for professionals in the field of data science and applications: artificial intelligence, big data, IoT, and blockchain. In summary, this book is expected to function as a helpful resource and manual, enabling readers to navigate the intricate domain of artificial intelligence, the Internet of things (IoT), and blockchain in smart environments. This book covers many topics related to integrating AI, IoT, blockchain, and smart environments. It begins by laying a solid foundation, introducing each technology's fundamental concepts and principles. Subsequent chapters explore applications and real-world use cases, demonstrating how AI, IoT, and blockchain can effectively address critical challenges within data science and applications.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 571
• Erscheinungstermin: 4. März 2024
• Englisch
• ISBN-13: 9783031484650
• Artikelnr.: 70121393

Inhaltsangabe

Sustainability in Internet of Things: Insights & Scope.- Machine Learning in Finance Case of Credit Scoring.- Prediction of coefficient of friction and wear rate of Stellite 6 coatings manufactured by LMD using Machine Learning.- Predicting Future Sales: A Machine Learning Algorithm Showdown.- A detailed study on the Game of Life.- A decision-making model for selecting solutions and improvement actions using fuzzy logic.- Sensored Brushless DC motor control based on an Artificial Neural Network controller.- A Machine Learning Based Approach to Analyze the Relationship Between Process Variables and Process Alarms.- Improving the Resolution of Images using Super-Resolution Generative Adversarial Networks.- Three Levels of Security Including Scrambling, Encryption and Embedding Data as Row in Cover Image with DNA Reference Sequence.