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Mathematical modeling
A logical problem-based introduction to the use of GeoGebra for mathematical modeling and problem solving within various areas of mathematics
A well-organized guide to mathematical modeling techniques for evaluating and solving problems in the diverse field of mathematics, Mathematical Modeling: Applications with GeoGebra presents a unique approach to software applications in GeoGebra and WolframAlpha. The software is well suited for modeling problems in numerous areas of mathematics including algebra, symbolic algebra, dynamic geometry, three-dimensional geometry, and statistics. Featuring detailed information on how GeoGebra can be used as a guide to mathematical modeling, the book provides comprehensive modeling examples that correspond to different levels of mathematical experience, from simple linear relations to differential equations.
Each chapter builds on the previous chapter with practical examples in order to illustrate the mathematical modeling skills necessary for problem solving. Addressing methods for evaluating models including relative error, correlation, square sum of errors, regression, and confidence interval, Mathematical Modeling: Applications with GeoGebra also includes:
* Over 400 diagrams and 300 GeoGebra examples with practical approaches to mathematical modeling that help the reader develop a full understanding of the content
* Numerous real-world exercises with solutions to help readers learn mathematical modeling techniques
* A companion website with GeoGebra constructions and screencasts
Mathematical Modeling: Applications with GeoGebrais ideal for upper-undergraduate and graduate-level courses in mathematical modeling, applied mathematics, modeling and simulation, operations research, and optimization. The book is also an excellent reference for undergraduate and high school instructors in mathematics.
eBook
Mathematics and computation in imaging science and information processing
The explosion of data arising from rapid advances in communication, sensing and computational power has concentrated research effort on more advanced techniques for the representation, processing, analysis and interpretation of data sets. In view of these exciting developments, the program “Mathematics and Computation in Imaging Science and Information Processing” was held at the Institute for Mathematical Sciences, National University of Singapore, from July to December 2003 and in August 2004 to promote and facilitate multidisciplinary research in the area. As part of the program, a series of tutorial lectures were conducted by international experts on a wide variety of topics in mathematical image, signal and information processing.
eBook
Introduction to Computational Modeling Using C and Open-Source Tools
This book presents the fundamental principles of computational models from a computer science perspective and explains how to implement the models using the C programming language. Emphasizing analytical skill development and problem solving, the book helps readers understand how to reason about and conceptualize the problems, generate mathematical formulations, and computationally visualize and solve the problems. It provides the foundation to understand more advanced scientific computing, including parallel computing using MPI, grid computing, and other techniques in high-performance computing.
eBook
Supply chain analytics and modelling : quantitative tools and applications
\"An incredible volume of data is generated at a very high speed within the supply chain and it is necessary to understand, use and effectively apply the knowledge learned from analyzing data using intelligent business models. However, practitioners and students in the field of supply chain management face a number of challenges when dealing with business models and mathematical modelling. Supply Chain Analytics and Modelling presents a range of business analytics models used within the supply chain to help readers develop knowledge on a variety of topics to overcome common issues. Supply Chain Analytics and Modelling covers areas including supply chain planning, single and multi-objective optimization, demand forecasting, product allocations, end-to-end supply chain simulation, vehicle routing and scheduling models. Learning is supported by case studies of specialist software packages for each example. Readers will also be provided with a critical view on how supply chain management performance measurement systems have been developed and supported by reliable and accurate data available in the supply chain. Online resources including lecturer slides are available\"-- Provided by publisher.
Book
Algorithms of Education
A critique of what lies behind the use of data in
contemporary education policy
While the science fiction tales of artificial intelligence
eclipsing humanity are still very much fantasies, in Algorithms
of Education the authors tell real stories of how algorithms
and machines are transforming education governance, providing a
fascinating discussion and critique of data and its role in
education policy.
Algorithms of Education explores how, for policy
makers, today's ever-growing amount of data creates the illusion of
greater control over the educational futures of students and the
work of school leaders and teachers. In fact, the increased
datafication of education, the authors argue, offers less and less
control, as algorithms and artificial intelligence further abstract
the educational experience and distance policy makers from teaching
and learning. Focusing on the changing conditions for education
policy and governance, Algorithms of Education proposes
that schools and governments are increasingly turning to \"synthetic
governance\"-a governance where what is human and machine becomes
less clear-as a strategy for optimizing education.
Exploring case studies of data infrastructures, facial
recognition, and the growing use of data science in education,
Algorithms of Education draws on a wide variety of
fields-from critical theory and media studies to science and
technology studies and education policy studies-mapping the
political and methodological directions for engaging with
datafication and artificial intelligence in education governance.
According to the authors, we must go beyond the debates that
separate humans and machines in order to develop new strategies
for, and a new politics of, education.
eBook
F♯ for quantitative finance
To develop your confidence in F#, this tutorial will first introduce you to simpler tasks such as curve fitting. You will then advance to more complex tasks such as implementing algorithms for trading semi-automation in a practical scenario-based format.If you are a data analyst or a practitioner in quantitative finance, economics, or mathematics and wish to learn how to use F# as a functional programming language, this book is for you. You should have a basic conceptual understanding of financial concepts and models. Elementary knowledge of the .NET framework would also be helpful.
eBook