Current Problems in Applied Mathematics and Computer Science and Systems (Paperback)

Anatoly Alikhanov

ISBN 10: 3031341260 / ISBN 13: 9783031341267

Published by Springer International Publishing AG, Cham, 2023

Paperback. This book is based on the best papers accepted for presentation during the International Conference on Actual Problems of Applied Mathematics and Computer Systems (APAMCS-2022), Russia. The book includes research materials on modern mathematical problems, solutions in the field of scientific computing, data analysis and modular computing. The scope of numerical methods in scientific computing presents original research, including mathematical models and software implementations, related to the following topics: numerical methods in scientific computing; solving optimization problems; methods for approximating functions, etc. The studies in data analysis and modular computing include contributions in the field of deep learning, neural networks, mathematical statistics, machine learning methods, residue number system and artificial intelligence. Finally, the book gives insights into the fundamental problems in mathematics education. The book intends for readership specializing in the field of scientific computing, parallel computing, computer technology, machine learning, information security and mathematical education. The scope of numerical methods in scientific computing presents original research, including mathematical models and software implementations, related to the following topics: numerical methods in scientific computing; Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9783031341267

Synopsis:

This book is based on the best papers accepted for presentation during the International Conference on Actual Problems of Applied Mathematics and Computer Systems (APAMCS-2022), Russia. The book includes research materials on modern mathematical problems, solutions in the field of scientific computing, data analysis and modular computing. The scope of numerical methods in scientific computing presents original research, including mathematical models and software implementations, related to the following topics: numerical methods in scientific computing; solving optimization problems; methods for approximating functions, etc. The studies in data analysis and modular computing include contributions in the field of deep learning, neural networks, mathematical statistics, machine learning methods, residue number system and artificial intelligence. Finally, the book gives insights into the fundamental problems in mathematics education. The book intends for readership specializing in the field of scientific computing, parallel computing, computer technology, machine learning, information security and mathematical education.

About the Author:

Anatoly Alikhanov has obtained his Ph.D. in Physical and Mathematical Sciences and is Vice-Rector for Scientific and Research work of the North Caucasus Federal University. He is the Head of the Regional Scientific and Educational Mathematical Center "North Caucasian Center for Mathematical Research." Earlier, he worked as Visiting Member of the dissertation council at Southeast University, Department of Mathematics, Nanjing, China. In 2016, he was invited for an internship in the field of numerical methods for solving fractional differential equations at the Nanjing University of China. А. Alikhanov is Member of the Editor Board of the Fractional Calculus and Applied Analysis Journal and Reviewer of over 30 reputable scientific journals in computational mathematics.

Pavel Lyakhov graduated in mathematics in Stavropol State University, in 2009, where he also received the Ph.D. degree in computer science, in 2012. He has been working at North-CaucasusFederal University, since 2012. He is currently the Head of the Department of Mathematical Modeling, North-Caucasus Federal University. His research interests include high-performance computing, quantum computing, residue number systems, digital signal processing, image processing and machine learning.

​Irina Samoylenko, PhD, Associate Professor at Informational Systems Department, Stavropol State Agrarian University, Russia. She received M.S. degree in Applied Mathematics and Informatics, PhD in System Analysis, Control and Processing of Information in North-Caucasus Federal University. Irina is a researcher in North-Caucasus Centre for Mathematical Research, North-Caucasus Federal University. She is a member of Association of Scientific Editors and Publishers, Russia. Her research interests include wireless sensor networks, IoT, optimization tasks and mathematical modeling. 

Bibliographic Details

Title: Current Problems in Applied Mathematics and ...
Publisher: Springer International Publishing AG, Cham
Publication Date: 2023
Binding: Paperback
Condition: new
Edition: 1st Edition