Advanced Computing In Industrial Mathematics

This book gathers the peer-reviewed proceedings of the 13th Annual Meeting of the Bulgarian Section of the Society for Industrial and Applied Mathematics, BGSIAM'18, held in Sofia, Bulgaria. The general theme of BGSIAM'18 was industrial and applied mathematics with particular focus on: mathematical physics, numerical analysis, high performance computing, optimization and control, mathematical biology, stochastic modeling, machine learning, digitization and imaging, advanced computing in environmental, biomedical and engineering applications.

This book presents recent research on Advanced Computing in Industrial Mathematics, which is one of the most prominent interdisciplinary areas and combines mathematics, computer science, scientific computations, engineering, physics, chemistry, medicine, etc. Further, the book presents the tools of Industrial Mathematics, which are based on mathematical models, and the corresponding computer codes, which are used to perform virtual experiments to obtain new data or to better understand the existing experimental results. The book gathers the peer-reviewed papers presented during the 10th Annual Meeting of the Bulgarian Section of SIAM (BGSIAM) from December 21 to 22, 2015 in Sofia, Bulgaria.

This book gathers the peer-reviewed proceedings of the 14th Annual Meeting of the Bulgarian Section of the Society for Industrial and Applied Mathematics, BGSIAM'19, held in Sofia, Bulgaria. The general theme of BGSIAM'19 was industrial and applied mathematics with particular focus on mathematical physics, numerical analysis, high-performance computing, optimization and control, mathematical biology, stochastic modeling, machine learning, digitization and imaging, and advanced computing in environmental, biomedical, and engineering applications.

This book gathers the peer-reviewed proceedings of the 12th Annual Meeting of the Bulgarian Section of the Society for Industrial and Applied Mathematics, BGSIAM’17, held in Sofia, Bulgaria, in December 2017. The general theme of BGSIAM’17 was industrial and applied mathematics, with a particular focus on: high-performance computing, numerical methods and algorithms, analysis of partial differential equations and their applications, mathematical biology, control and uncertain systems, stochastic models, molecular dynamics, neural networks, genetic algorithms, metaheuristics for optimization problems, generalized nets, and Big Data.

This book gathers the peer-reviewed proceedings of the 15th Annual Meeting of the Bulgarian Section of the Society for Industrial and Applied Mathematics, BGSIAM'20, held in Sofia, Bulgaria. The general theme of BGSIAM'20 was industrial and applied mathematics with particular focus on mathematical physics, numerical analysis, high-performance computing, optimization and control, mathematical biology, stochastic modeling, machine learning, digitization and imaging, advanced computing in environmental, and biomedical and engineering applications.

This book presents recent research on Advanced Computing in Industrial Mathematics, which is one of the most prominent interdisciplinary areas, bringing together mathematics, computer science, scientific computations, engineering, physics, chemistry, medicine, etc. Further, the book presents the major tools used in Industrial Mathematics, which are based on mathematical models, and the corresponding computer codes, which are used to perform virtual experiments to obtain new data or to better understand previous experimental findings. The book gathers the peer-reviewed papers presented at the 11th Annual Meeting of the Bulgarian Section of SIAM (BGSIAM), from December 20 to 22, 2016 in Sofia, Bulgaria.

This book gathers the peer-reviewed proceedings of the 12th Annual Meeting of the Bulgarian Section of the Society for Industrial and Applied Mathematics, BGSIAM'17, held in Sofia, Bulgaria, in December 2017. The general theme of BGSIAM'17 was industrial and applied mathematics, with a particular focus on: high-performance computing, numerical methods and algorithms, analysis of partial differential equations and their applications, mathematical biology, control and uncertain systems, stochastic models, molecular dynamics, neural networks, genetic algorithms, metaheuristics for optimization problems, generalized nets, and Big Data.

This book is devoted to some analytical and numerical methods for analyzing industrial problems related to emerging technologies such as digital image processing, material sciences and financial derivatives affecting banking and financial institutions. Case studies are based on industrial projects given by reputable industrial organizations of Europe to the Institute of Industrial and Business Mathematics, Kaiserslautern, Germany. Mathematical methods presented in the book which are most reliable for understanding current industrial problems include Iterative Optimization Algorithms, Galerkin's Method, Finite Element Method, Boundary Element Method, Quasi-Monte Carlo Method, Wavelet Analysis, and Fractal Analysis. The Black-Scholes model of Option Pricing, which was awarded the 1997 Nobel Prize in Economics, is presented in the book. In addition, basic concepts related to modeling are incorporated in the book. Audience: The book is appropriate for a course in Industrial Mathematics for upper-level undergraduate or beginning graduate-level students of mathematics or any branch of engineering.

This volume is the first of two containing selected papers from the International Conference on Advances in Mathematical Sciences (ICAMS), held at the Vellore Institute of Technology in December 2017. This meeting brought together researchers from around the world to share their work, with the aim of promoting collaboration as a means of solving various problems in modern science and engineering. The authors of each chapter present a research problem, techniques suitable for solving it, and a discussion of the results obtained. These volumes will be of interest to both theoretical- and application-oriented individuals in academia and industry. Papers in Volume I are dedicated to active and open areas of research in algebra, analysis, operations research, and statistics, and those of Volume II consider differential equations, fluid mechanics, and graph theory.

This book deals with computer performance by addressing basic preconditions. Besides general considerations about performance, several new approaches are presented. One of them targets memory structures by introducing the possibility of overlapping non-interfering (virtual) address spaces. This approach is based on a newly developed jump transformation between different symbol spaces. Another approach deals with efficiency and accuracy in scientific calculations. Finally the concept of a Neural Relational Data Base Management System is introduced and the performance potential of quantum computers assessed.