Artificial Intelligence Modeling for Dynamical Problems

Erscheinungsjahr 2027
ISBN: 978-0-443-49134-4
Verlag: Elsevier Science

Buch, Englisch, 250 Seiten, Format (B × H): 191 mm x 235 mm

Artificial Intelligence Modeling for Dynamical Problems provides a comprehensive exploration of AI-driven methodologies tailored to address the intricate challenges posed by dynamical systems. The chapters in this book delve into cutting-edge techniques, including scientific machine learning, operator learning, fuzzy logic, and optimization algorithms, highlighting their applications in structural dynamics, fluid dynamics, robotics, and wave dynamics. Readers will gain insights into innovative state-of-the-art approaches such as Physics-Informed Neural Networks (PINNs) for precise navigation and control in autonomous vehicles, convolutional neural networks (CNNs) for frequency dynamics recognition, and data-driven models for market sentiment analysis. Additionally, the book explores the role of uncertainty modeling, statistical inference, and hybrid AI techniques, such as Type-2 fuzzy fractional modeling, in advancing the field of dynamical system analysis. Each chapter combines foundational principles with practical applications, including recent investigations, making it a valuable resource for researchers, practitioners, students of STEM seeking to apply theoretical AI models to real-world dynamical problems.

Autoren/Hrsg.

Chakraverty, Snehashish

Mohapatra, Dhabaleswar

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
• Mathematik | Informatik Mathematik Mathematische Analysis
• Mathematik | Informatik Mathematik Mathematik Allgemein Diskrete Mathematik, Kombinatorik

Inhaltsverzeichnis

1. Neural Network Modeling for Dynamical Systems
2. Scientific Machine Learning for Fluid Dynamics
3. Optimization Techniques for Dynamical Models
4. Fuzzy Models for Structural Dynamics
5. Type-2 Fuzzy Fractional Modeling
6. Uncertainty Analysis in Wave Dynamics
7. Lightweight Robotics Modeling
8. Physics-informed Machine Learning for Robot Tracking Control
9. Neural Networks Model for Navigation Systems
10. Deep Learning for Remote Sensing Applications
11. Data-Driven Models for Financial Analysis
12. CNNs for Bioinformatics Applications
13. Deep CNNs for Frequency Dynamics Recognition
14. Data Mining for Market Sentiment Analysis
15. Statistical Inference for Dynamical Systems
16. Machine Learning in Poverty Alleviation Dynamics

Über Autor(innen)

Mohapatra, Dhabaleswar
Dhabaleswar Mohapatra is currently working as an Assistant Professor in the Department of Mathematics at the Institute of Technical Education and Research, Siksha ‘O’ Anusandhan (Deemed to be University), Odisha, India. He received his PhD from the National Institute of Technology, Rourkela, Odisha, India. To date, he has published 12 research articles in journals and book chapters.

Chakraverty, Snehashish
Dr. Snehashish Chakraverty is a Senior Professor in the Department of Mathematics (Applied Mathematics Group), National Institute of Technology Rourkela, with over 30 years of teaching and research experience. A gold medalist from the University of Roorkee (now IIT Roorkee), he earned his Ph.D. from IIT Roorkee and completed post-doctoral work at the University of Southampton (UK) and Concordia University (Canada). He has also served as a visiting professor in Canada and South Africa. Dr. Chakraverty has authored/edited 38 books and published over 495 research papers. His research spans differential equations (ordinary, partial, fractional), numerical and computational methods, structural and fluid dynamics, uncertainty modeling, and soft computing techniques. He has guided 27 Ph.D. scholars, with 10 currently under his supervision.

He has led 16 funded research projects and hosted international researchers through prestigious fellowships. Recognized in the top 2% of scientists globally (Stanford-Elsevier list, 2020–2024), he has received numerous awards including the CSIR Young Scientist Award, BOYSCAST Fellowship, INSA Bilateral Exchange, and IOP Top Cited Paper Awards. He is Chief Editor of International Journal of Fuzzy Computation and Modelling and serves on several international editorial boards.