This volume brings forth a set of papers presented at the conference on "e;Varia- tional Inequalities and network equilibrium problems"e;, held in Erice at the "e;G.
Employ essential tools and functions of the MATLAB and Simulink packages, which are explained and demonstrated via interactive examples and case studies.
Employ the essential and hands-on tools and functions of MATLAB's ordinary differential equation (ODE) and partial differential equation (PDE) packages, which are explained and demonstrated via interactive examples and case studies.
Discover how to use the popular RStudio IDE as a professional tool that includes code refactoring support, debugging, and Git version control integration.
Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and data mining.
Employ essential and hands-on tools and functions of the MATLAB and Simulink packages, which are explained and demonstrated via interactive examples and case studies.
Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R.
Assess the quality of your prediction and classification models in ways that accurately reflect their real-world performance, and then improve this performance using state-of-the-art algorithms such as committee-based decision making, resampling the dataset, and boosting.
Learn how to write object-oriented programs in R and how to construct classes and class hierarchies in the three object-oriented systems available in R.
Examine business problems and use a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language.
Learn the fundamental aspects of the business statistics, data mining, and machine learning techniques required to understand the huge amount of data generated by your organization.
SPSS (The Statistical Package for the Social Sciences) is a computer program which enables data from surveys and experiments to be analyzed fully and flexibly.
Industrial, financial, commercial or any kinds of project have at least one common feature: the better organized they are, the higher the profit or the lower the cost.
Monte Carlo statistical methods, particularly those based on Markov chains, are now an essential component of the standard set of techniques used by statisticians.
A substantial portion of this book is a revised version of Discrete Event Systems: Modeling and Performance Analysis (1993), which was written by the first author and received the 1999 Harold Chestnut Prize, awarded by the International Federation of Automatic Control (IFAC) for best control engineering textbook.
In this book the details of many calculations are provided for access to work in quantum groups, algebraic differential calculus, noncommutative geometry, fuzzy physics, discrete geometry, gauge theory, quantum integrable systems, braiding, finite topological spaces, some aspects of geometry and quantum mechanics and gravity.
Since the outstanding and pioneering research work of Hopfield on recurrent neural networks (RNNs) in the early 80s of the last century, neural networks have rekindled strong interests in scientists and researchers.
When elementary courses in discrete and combinatorial mathematics first became popular, they usually covered a broad spectrumofpure and applied topics.
Communications, Information and Network Security is an excellent reference for both professional and academic researchers in the field of communication.
Many important problems in applied science and engineering, such as the Navier- Stokes equations in fluid dynamics, the primitive equations in global climate mod- eling, the strain-stress equations in mechanics, the neutron diffusion equations in nuclear engineering, and MRIICT medical simulations, involve complicated sys- tems of nonlinear partial differential equations.
