Modeling with Data: Tools and Techniques for Scientific Computing
by Ben Klemens
Publisher: Princeton University Press 2009
Number of pages: 470
The book fully explains how to execute computationally intensive analysis on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results. Ben Klemens introduces a set of open and unlimited tools, and uses them to demonstrate data management, analysis, and simulation techniques essential for dealing with large data sets and computationally intensive procedures. Modeling with Data will interest anyone looking for a comprehensive guide to these powerful statistical tools, including researchers and graduate students in the social sciences, biology, engineering, economics, and applied mathematics.
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by Shkelzen Cakaj - InTech
Topics covered: parametric representation of shapes, modeling of dynamic continuous fluid flow process, plant layout optimal plot plan, atmospheric modeling, cellular automata simulations, thyristor switching characteristics simulation, etc.
This book helps you to start modeling with AnyLogic -- a multi-method simulation modeling tool that supports different modeling techniques. Topics covered: Agent-Based Modeling; System Dynamics; Discrete Event Simulation; Pedestrian Simulation.
by Norm Matloff - University of California, Davis
The materials here form a textbook for a course in mathematical probability and statistics for computer science students. Computer science examples are used throughout, in areas such as: computer networks; data and text mining; computer security...
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Presents new modelling and analysis techniques for the description of discrete event dynamic systems. Created within the text is a calculus which allows the derivation of analytical tools for computing the time behavior of this type of system.