Search Results for "modeling-with-data-tools-and-techniques-for-scientific-computing"

Modeling with Data

Modeling with Data

Tools and Techniques for Scientific Computing

  • Author: Ben Klemens
  • Publisher: Princeton University Press
  • ISBN: 9781400828746
  • Category: Mathematics
  • Page: 472
  • View: 5148
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Modeling with Data fully explains how to execute computationally intensive analyses 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. He then demonstrates how to easily apply these tools to the many threads of statistical technique, including classical, Bayesian, maximum likelihood, and Monte Carlo methods. Klemens's accessible survey describes these models in a unified and nontraditional manner, providing alternative ways of looking at statistical concepts that often befuddle students. The book includes nearly one hundred sample programs of all kinds. Links to these programs will be available on this page at a later date. 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.

Mastering Scientific Computing with R

Mastering Scientific Computing with R

  • Author: Paul Gerrard,Radia M. Johnson
  • Publisher: Packt Publishing Ltd
  • ISBN: 1783555262
  • Category: Computers
  • Page: 432
  • View: 6407
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If you want to learn how to quantitatively answer scientific questions for practical purposes using the powerful R language and the open source R tool ecosystem, this book is ideal for you. It is ideally suited for scientists who understand scientific concepts, know a little R, and want to be able to start applying R to be able to answer empirical scientific questions. Some R exposure is helpful, but not compulsory.

Efficient Numerical Methods and Information-Processing Techniques for Modeling Hydro- and Environmental Systems

Efficient Numerical Methods and Information-Processing Techniques for Modeling Hydro- and Environmental Systems

  • Author: Reinhard Hinkelmann
  • Publisher: Springer Science & Business Media
  • ISBN: 9783540241461
  • Category: Science
  • Page: 306
  • View: 5760
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Numerical simulation models have become indispensable in hydro- and environmental sciences and engineering. This monograph presents a general introduction to numerical simulation in environment water, based on the solution of the equations for groundwater flow and transport processes, for multiphase and multicomponent flow and transport processes in the subsurface as well as for flow and transport processes in surface waters. It displays in detail the state of the art of discretization and stabilization methods (e.g. finite-difference, finite-element, and finite-volume methods), parallel methods, and adaptive methods as well as fast solvers, with particular focus on explaining the interactions of the different methods. The book gives a brief overview of various information-processing techniques and demonstrates the interactions of the numerical methods with the information-processing techniques, in order to achieve efficient numerical simulations for a wide range of applications in environment water.

Data Analysis with Open Source Tools

Data Analysis with Open Source Tools

A Hands-On Guide for Programmers and Data Scientists

  • Author: Philipp K. Janert
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 9781449396657
  • Category: Computers
  • Page: 540
  • View: 9626
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Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications. Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you. Use graphics to describe data with one, two, or dozens of variables Develop conceptual models using back-of-the-envelope calculations, as well asscaling and probability arguments Mine data with computationally intensive methods such as simulation and clustering Make your conclusions understandable through reports, dashboards, and other metrics programs Understand financial calculations, including the time-value of money Use dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situations Become familiar with different open source programming environments for data analysis "Finally, a concise reference for understanding how to conquer piles of data."--Austin King, Senior Web Developer, Mozilla "An indispensable text for aspiring data scientists."--Michael E. Driscoll, CEO/Founder, Dataspora

Advances in Data-based Approaches for Hydrologic Modeling and Forecasting

Advances in Data-based Approaches for Hydrologic Modeling and Forecasting

  • Author: Bellie Sivakumar,Ronny Berndtsson
  • Publisher: World Scientific
  • ISBN: 9814307971
  • Category: Science
  • Page: 519
  • View: 7786
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This book comprehensively accounts the advances in data-based approaches for hydrologic modeling and forecasting. Eight major and most popular approaches are selected, with a chapter for each stochastic methods, parameter estimation techniques, scaling and fractal methods, remote sensing, artificial neural networks, evolutionary computing, wavelets, and nonlinear dynamics and chaos methods. These approaches are chosen to address a wide range of hydrologic system characteristics, processes, and the associated problems. Each of these eight approaches includes a comprehensive review of the fundamental concepts, their applications in hydrology, and a discussion on potential future directions.

Data-Driven Modeling & Scientific Computation

Data-Driven Modeling & Scientific Computation

Methods for Complex Systems & Big Data

  • Author: J. Nathan Kutz
  • Publisher: OUP Oxford
  • ISBN: 019163588X
  • Category: Mathematics
  • Page: 608
  • View: 9168
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The burgeoning field of data analysis is expanding at an incredible pace due to the proliferation of data collection in almost every area of science. The enormous data sets now routinely encountered in the sciences provide an incentive to develop mathematical techniques and computational algorithms that help synthesize, interpret and give meaning to the data in the context of its scientific setting. A specific aim of this book is to integrate standard scientific computing methods with data analysis. By doing so, it brings together, in a self-consistent fashion, the key ideas from: · statistics, · time-frequency analysis, and · low-dimensional reductions The blend of these ideas provides meaningful insight into the data sets one is faced with in every scientific subject today, including those generated from complex dynamical systems. This is a particularly exciting field and much of the final part of the book is driven by intuitive examples from it, showing how the three areas can be used in combination to give critical insight into the fundamental workings of various problems. Data-Driven Modeling and Scientific Computation is a survey of practical numerical solution techniques for ordinary and partial differential equations as well as algorithms for data manipulation and analysis. Emphasis is on the implementation of numerical schemes to practical problems in the engineering, biological and physical sciences. An accessible introductory-to-advanced text, this book fully integrates MATLAB and its versatile and high-level programming functionality, while bringing together computational and data skills for both undergraduate and graduate students in scientific computing.

Intelligent Techniques and Tools for Novel System Architectures

Intelligent Techniques and Tools for Novel System Architectures

  • Author: Panagiotis Chountas,Ilias Petrounias
  • Publisher: Springer Science & Business Media
  • ISBN: 3540776214
  • Category: Mathematics
  • Page: 548
  • View: 7414
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This volume presents new directions and solutions in broadly perceived intelligent systems. An urgent need this volume has occurred as a result of vivid discussions and presentations at the "IEEE-IS’ 2006 – The 2006 Third International IEEE Conference on Intelligent Systems" held in London, UK, September, 2006. This book is a compilation of many valuable inspiring works written by both the conference participants and some other experts in this new and challenging field.

Proceedings of the 8th Python in Science Conference

Proceedings of the 8th Python in Science Conference

  • Author: GaeÌl Varoquaux,Stéfan van der Walt,K. Jarrod Millman
  • Publisher: Lulu.com
  • ISBN: 0557232120
  • Category:
  • Page: 92
  • View: 7429
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The proceedings of the 8th annual Python for Scientific Computing conference.

Modeling Methods for Marine Science

Modeling Methods for Marine Science

  • Author: David M. Glover,William J. Jenkins,Scott C. Doney
  • Publisher: Cambridge University Press
  • ISBN: 1139500716
  • Category: Science
  • Page: N.A
  • View: 3443
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This advanced textbook on modeling, data analysis and numerical techniques for marine science has been developed from a course taught by the authors for many years at the Woods Hole Oceanographic Institute. The first part covers statistics: singular value decomposition, error propagation, least squares regression, principal component analysis, time series analysis and objective interpolation. The second part deals with modeling techniques: finite differences, stability analysis and optimization. The third part describes case studies of actual ocean models of ever increasing dimensionality and complexity, starting with zero-dimensional models and finishing with three-dimensional general circulation models. Throughout the book hands-on computational examples are introduced using the MATLAB programming language and the principles of scientific visualization are emphasised. Ideal as a textbook for advanced students of oceanography on courses in data analysis and numerical modeling, the book is also an invaluable resource for a broad range of scientists undertaking modeling in chemical, biological, geological and physical oceanography.

Computational Methods for Optimizing Manufacturing Technology: Models and Techniques

Computational Methods for Optimizing Manufacturing Technology: Models and Techniques

Models and Techniques

  • Author: Davim, J. Paulo
  • Publisher: IGI Global
  • ISBN: 1466601299
  • Category: Technology & Engineering
  • Page: 395
  • View: 9684
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"This book contains the latest research developments in manufacturing technology and its optimization, and demonstrates the fundamentals of new computational approaches and the range of their potential application"--Provided by publisher.