Pavel Lyakhov – författare

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.

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.

This book based on the best papers accepted for presentation during the International Conference on Current Problems of Applied Mathematics and Computer Systems (CPAMCS-2024), Russia. This book includes research focused on contemporary mathematical challenges and their resolutions within scientific computing, data analysis and modular computing. This book presents original studies on numerical methods in scientific computing, optimization problem-solving, function approximation techniques, among other topics. Furthermore, it encompasses research contributions in data analysis and modular computing, highlighting advancements in deep learning, neural networks, mathematical statistics, machine learning techniques, residue number systems and artificial intelligence. Additionally, this book addresses critical issues in mathematical education. This book intends for professionals engaged in scientific computing, parallel computing, computer technology, machine learning, information security, and mathematics education.