Author: Ramin Madarshahian Publisher: Springer Nature ISBN: 3031041224 Category : Computers Languages : en Pages : 158
Book Description
Data Science in Engineering, Volume 9: Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022, the nineth volume of nine from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Data Science in Engineering, including papers on: Novel Data-driven Analysis Methods Deep Learning Gaussian Process Analysis Real-time Video-based Analysis Applications to Nonlinear Dynamics and Damage Detection High-rate Structural Monitoring and Prognostics
Author: Ramin Madarshahian Publisher: Springer Nature ISBN: 3031349466 Category : Computers Languages : en Pages : 185
Book Description
Data Science in Engineering, Volume 10: Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics, 2023, the tenth volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Data Science in Engineering, including papers on: Novel Data-driven Analysis Methods Deep Learning Gaussian Process Analysis Real-time Video-based Analysis Applications to Nonlinear Dynamics and Damage Detection High-rate Structural Monitoring and Prognostics
Author: Shuichi Fukuda Publisher: Springer Nature ISBN: 3031058674 Category : Technology & Engineering Languages : en Pages : 190
Book Description
This is the latest volume in the series of Springer titles on emotional engineering tracking the development of this field. Engineering has been based on the Euclidean space approach and it was numerical data-centric. In short, our engineering up to now has been control-based, i.e., on tactics and problem solving. When we realize AI consumes 10,000 times more energy than human brain, we understand how it is better to use 10,000 people’s minds. But current society is industrial society. The industrial revolution introduced division of labour and we started to work for others. But the tremendous consumption of energy indicates that we need to move toward another society. If we can make the next society a self-Satisfying society (SSS) and create a new sustainable society with greater mental wellbeing then many emerging problems will be solved and we can enjoy our lives better. Emotional engineering engages with this challenge.
Author: Ramin Madarshahian Publisher: Springer Nature ISBN: 3030760049 Category : Technology & Engineering Languages : en Pages : 287
Book Description
Data Science and Engineering Volume 9: Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics, 2021, the ninth volume of nine from the Conference, brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Data Science in Engineering, including papers on: Data Science in Engineering Applications Engineering Mathematics Computational Methods in Engineering
Author: Zdzislaw Polkowski Publisher: CRC Press ISBN: 1000520846 Category : Technology & Engineering Languages : en Pages : 159
Book Description
This book brings insight into data science and offers applications and implementation strategies. It includes current developments and future directions and covers the concept of data science along with its origins. It focuses on the mechanisms of extracting data along with classifications, architectural concepts, and business intelligence with predictive analysis. Data Science in Engineering and Management: Applications, New Developments, and Future Trends introduces the concept of data science, its use, and its origins, as well as presenting recent trends, highlighting future developments; discussing problems and offering solutions. It provides an overview of applications on data linked to engineering and management perspectives and also covers how data scientists, analysts, and program managers who are interested in productivity and improving their business can do so by incorporating a data science workflow effectively. This book is useful to researchers involved in data science and can be a reference for future research. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.
Author: Steven L. Brunton Publisher: Cambridge University Press ISBN: 1009098489 Category : Computers Languages : en Pages : 615
Book Description
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Author: Kukatlapalli Pradeep Kumar Publisher: John Wiley & Sons ISBN: 1119841976 Category : Mathematics Languages : en Pages : 367
Book Description
DATA ENGINEERING and DATA SCIENCE Written and edited by one of the most prolific and well-known experts in the field and his team, this exciting new volume is the “one-stop shop” for the concepts and applications of data science and engineering for data scientists across many industries. The field of data science is incredibly broad, encompassing everything from cleaning data to deploying predictive models. However, it is rare for any single data scientist to be working across the spectrum day to day. Data scientists usually focus on a few areas and are complemented by a team of other scientists and analysts. Data engineering is also a broad field, but any individual data engineer doesn’t need to know the whole spectrum of skills. Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. For all the work that data scientists do to answer questions using large sets of information, there have to be mechanisms for collecting and validating that information. In this exciting new volume, the team of editors and contributors sketch the broad outlines of data engineering, then walk through more specific descriptions that illustrate specific data engineering roles. Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This book brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.
Author: Arif Ahmed Sk Publisher: Springer Nature ISBN: 303122485X Category : Computers Languages : en Pages : 347
Book Description
This book constitutes the refereed proceedings of the First International Symposium on Artificial Intelligence, ISAI 2022, held in Haldia, India, during February 17-22, 2022. The 30 full papers included in this book were carefully reviewed and selected from 75 submissions. They were organized in topical sections as follows: information systems, mathematics and data analyses; and applied artificial intelligence. .
Author: Ramin Madarshahian
Author: Ramin Madarshahian
Author: Shuichi Fukuda
Author: Ramin Madarshahian
Author: Zdzislaw Polkowski
Author: Steven L. Brunton
Author: Kukatlapalli Pradeep Kumar
Author: KMCT College of Engineering for Women
Author: Erik Blasch
Author: Arif Ahmed Sk