Modeling and Simulation in Ecotoxicology with Applications in MATLAB and Simulink PDF Download

Author: Kenneth R. Dixon
Publisher: CRC Press
ISBN: 1439855188
Category : Mathematics
Languages : en
Pages : 270

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Book Description
Exploring roles critical to environmental toxicology, Modeling and Simulation in Ecotoxicology with Applications in MATLAB and Simulink covers the steps in modeling and simulation from problem conception to validation and simulation analysis. Using the MATLAB and Simulink programming languages, the book presents examples of mathematical functions a

Author: Angela Dean
Publisher: CRC Press
ISBN: 146650434X
Category : Mathematics
Languages : en
Pages : 946

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Book Description
This carefully edited collection synthesizes the state of the art in the theory and applications of designed experiments and their analyses. It provides a detailed overview of the tools required for the optimal design of experiments and their analyses. The handbook covers many recent advances in the field, including designs for nonlinear models and algorithms applicable to a wide variety of design problems. It also explores the extensive use of experimental designs in marketing, the pharmaceutical industry, engineering and other areas.

Author: L. Ashok Kumar
Publisher: Elsevier
ISBN: 0443298890
Category : Science
Languages : en
Pages : 109

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Book Description
Predictive Analytics using MATLAB(R) for Biomedical Applications is a comprehensive and practical guide for biomedical engineers, data scientists, and researchers on how to use predictive analytics techniques in MATLAB(R) for solving real-world biomedical problems. The book offers a technical overview of various predictive analytics methods and covers the utilization of MATLAB(R) for implementing these techniques. It includes several case studies that demonstrate how predictive analytics can be applied to real-world biomedical problems, such as predicting disease progression, analyzing medical imaging data, and optimizing treatment outcomes.With a plethora of examples and exercises, this book is the ultimate tool for reinforcing one's knowledge and skills. - Covers various predictive analytics methods, including regression analysis, time series analysis, and machine learning algorithms, providing readers with a comprehensive understanding of the field - Provides a hands-on approach to learning predictive analytics, with a focus on practical applications in biomedical engineering - Includes several case studies that demonstrate the practical application of predictive analytics in real-world biomedical problems, such as disease progression prediction, medical imaging analysis, and treatment optimization

Author: Da-Wei Gu
Publisher: Springer Science & Business Media
ISBN: 1846280915
Category : Technology & Engineering
Languages : en
Pages : 393

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Book Description
Shows readers how to exploit the capabilities of the MATLAB® Robust Control and Control Systems Toolboxes to the fullest using practical robust control examples.

Author: Andrew Metcalfe
Publisher: CRC Press
ISBN: 1439895481
Category : Mathematics
Languages : en
Pages : 811

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Book Description
Engineers are expected to design structures and machines that can operate in challenging and volatile environments, while allowing for variation in materials and noise in measurements and signals. Statistics in Engineering, Second Edition: With Examples in MATLAB and R covers the fundamentals of probability and statistics and explains how to use these basic techniques to estimate and model random variation in the context of engineering analysis and design in all types of environments. The first eight chapters cover probability and probability distributions, graphical displays of data and descriptive statistics, combinations of random variables and propagation of error, statistical inference, bivariate distributions and correlation, linear regression on a single predictor variable, and the measurement error model. This leads to chapters including multiple regression; comparisons of several means and split-plot designs together with analysis of variance; probability models; and sampling strategies. Distinctive features include: All examples based on work in industry, consulting to industry, and research for industry Examples and case studies include all engineering disciplines Emphasis on probabilistic modeling including decision trees, Markov chains and processes, and structure functions Intuitive explanations are followed by succinct mathematical justifications Emphasis on random number generation that is used for stochastic simulations of engineering systems, demonstration of key concepts, and implementation of bootstrap methods for inference Use of MATLAB and the open source software R, both of which have an extensive range of statistical functions for standard analyses and also enable programing of specific applications Use of multiple regression for times series models and analysis of factorial and central composite designs Inclusion of topics such as Weibull analysis of failure times and split-plot designs that are commonly used in industry but are not usually included in introductory textbooks Experiments designed to show fundamental concepts that have been tested with large classes working in small groups Website with additional materials that is regularly updated Andrew Metcalfe, David Green, Andrew Smith, and Jonathan Tuke have taught probability and statistics to students of engineering at the University of Adelaide for many years and have substantial industry experience. Their current research includes applications to water resources engineering, mining, and telecommunications. Mahayaudin Mansor worked in banking and insurance before teaching statistics and business mathematics at the Universiti Tun Abdul Razak Malaysia and is currently a researcher specializing in data analytics and quantitative research in the Health Economics and Social Policy Research Group at the Australian Centre for Precision Health, University of South Australia. Tony Greenfield, formerly Head of Process Computing and Statistics at the British Iron and Steel Research Association, is a statistical consultant. He has been awarded the Chambers Medal for outstanding services to the Royal Statistical Society; the George Box Medal by the European Network for Business and Industrial Statistics for Outstanding Contributions to Industrial Statistics; and the William G. Hunter Award by the American Society for Quality.

Author: Thomas J. Santner
Publisher: Springer
ISBN: 1493988476
Category : Mathematics
Languages : en
Pages : 446

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Book Description
This book describes methods for designing and analyzing experiments that are conducted using a computer code, a computer experiment, and, when possible, a physical experiment. Computer experiments continue to increase in popularity as surrogates for and adjuncts to physical experiments. Since the publication of the first edition, there have been many methodological advances and software developments to implement these new methodologies. The computer experiments literature has emphasized the construction of algorithms for various data analysis tasks (design construction, prediction, sensitivity analysis, calibration among others), and the development of web-based repositories of designs for immediate application. While it is written at a level that is accessible to readers with Masters-level training in Statistics, the book is written in sufficient detail to be useful for practitioners and researchers. New to this revised and expanded edition: • An expanded presentation of basic material on computer experiments and Gaussian processes with additional simulations and examples • A new comparison of plug-in prediction methodologies for real-valued simulator output • An enlarged discussion of space-filling designs including Latin Hypercube designs (LHDs), near-orthogonal designs, and nonrectangular regions • A chapter length description of process-based designs for optimization, to improve good overall fit, quantile estimation, and Pareto optimization • A new chapter describing graphical and numerical sensitivity analysis tools • Substantial new material on calibration-based prediction and inference for calibration parameters • Lists of software that can be used to fit models discussed in the book to aid practitioners

Author: Devendra K. Chaturvedi
Publisher: CRC Press
ISBN: 143980673X
Category : Computers
Languages : en
Pages : 734

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Book Description
Not only do modeling and simulation help provide a better understanding of how real-world systems function, they also enable us to predict system behavior before a system is actually built and analyze systems accurately under varying operating conditions. Modeling and Simulation of Systems Using MATLAB® and Simulink® provides comprehensive, state-of-the-art coverage of all the important aspects of modeling and simulating both physical and conceptual systems. Various real-life examples show how simulation plays a key role in understanding real-world systems. The author also explains how to effectively use MATLAB and Simulink software to successfully apply the modeling and simulation techniques presented. After introducing the underlying philosophy of systems, the book offers step-by-step procedures for modeling different types of systems using modeling techniques, such as the graph-theoretic approach, interpretive structural modeling, and system dynamics modeling. It then explores how simulation evolved from pre-computer days into the current science of today. The text also presents modern soft computing techniques, including artificial neural networks, fuzzy systems, and genetic algorithms, for modeling and simulating complex and nonlinear systems. The final chapter addresses discrete systems modeling. Preparing both undergraduate and graduate students for advanced modeling and simulation courses, this text helps them carry out effective simulation studies. In addition, graduate students should be able to comprehend and conduct simulation research after completing this book.

Author: Sandip Kumar Saha
Publisher: Springer Nature
ISBN: 9811583153
Category : Technology & Engineering
Languages : en
Pages : 644

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Book Description
This volume presents selected papers from the 7th International Congress on Computational Mechanics and Simulation held at IIT Mandi, India. The papers discuss the development of mathematical models representing physical phenomena and applying modern computing methods and simulations to analyse them. The studies cover recent advances in the fields of nano mechanics and biomechanics, simulations of multiscale and multiphysics problems, developments in solid mechanics and finite element method, advancements in computational fluid dynamics and transport phenomena, and applications of computational mechanics and techniques in emerging areas. The volume will be of interest to researchers and academics from civil engineering, mechanical engineering, aerospace engineering, materials engineering/science, physics, mathematics and other disciplines.

Author: Colleen Spiegel
Publisher: Elsevier
ISBN: 0080559018
Category : Computers
Languages : en
Pages : 454

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Book Description
Although, the basic concept of a fuel cell is quite simple, creating new designs and optimizing their performance takes serious work and a mastery of several technical areas. PEM Fuel Cell Modeling and Simulation Using Matlab, provides design engineers and researchers with a valuable tool for understanding and overcoming barriers to designing and building the next generation of PEM Fuel Cells. With this book, engineers can test components and verify designs in the development phase, saving both time and money. Easy to read and understand, this book provides design and modelling tips for fuel cell components such as: modelling proton exchange structure, catalyst layers, gas diffusion, fuel distribution structures, fuel cell stacks and fuel cell plant. This book includes design advice and MATLAB and FEMLAB codes for Fuel Cell types such as: polymer electrolyte, direct methanol and solid oxide fuel cells. This book also includes types for one, two and three dimensional modeling and two-phase flow phenomena and microfluidics. *Modeling and design validation techniques *Covers most types of Fuel Cell including SOFC *MATLAB and FEMLAB modelling codes *Translates basic phenomena into mathematical equations

Author: Russell R. Barton
Publisher: Springer Science & Business Media
ISBN: 1461213983
Category : Mathematics
Languages : en
Pages : 200

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Book Description
Most texts on the design of experiments focus on the analysis of experimental data, not on the creation of the design. Graphical Methods for Experimental Design presents a strategic view of the planning of experiments, and provides a number of graphical tools that are useful for justifying the effort required for experimentation, identifying variables and candidate statistical models, selecting the set of run conditions and for assessing the quality of the design. In addition, the graphical framework for creating fractional factorial designs is used to present experimental results in a way that is easier to understand than a set of model coefficients. The text merely assumes a basic knowledge of statistics and matrices, while many of the graphical techniques are accessible without any knowledge of statistical models, requiring only some familiarity with the plotting of functions and with the concept of projection from elementary mechanical drawing.