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    Applied Numerical Methods with Python for Engineers and Scientists

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    Applied Numerical Methods with Python for Engineers and Scientists

    • Chapra Àú
    • McGraw-Hill
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    Chapra

    ÀúÀÚ : Steven C. Chapra
    Steve Chapra is the Emeritus Professor and Emeritus Berger Chair in the Civil and Environmental Engineering Department at Tufts University. His other books include Surface Water-Quality Modeling, Numerical Methods for Engineers, and Applied Numerical Methods with Python. Dr. Chapra received engineering degrees from Manhattan College and the University of Michigan. Before joining Tufts, he worked for the U.S. Environmental Protection Agency and the National Oceanic and Atmospheric Administration, and taught at Texas A&M University, the University of Colorado, and Imperial College London. His general research interests focus on surface water-quality modeling and advanced computer applications in environmental engineering. He is a Fellow and Life Member of the American Society of Civil Engineering (ASCE) and has received many awards for his scholarly and academic contributions, including the Rudolph Hering Medal (ASCE) for his research, and the Meriam-Wiley Distinguished Author Award (American Society for Engineering Education). He has also been recognized as an outstanding teacher and advisor among the engineering faculties at Texas A&M University, the University of Colorado, and Tufts University. As a strong proponent of continuing education, he has also taught over 90 workshops for professionals on numerical methods, computer programming, and environmental modeling.Beyond his professional interests, he enjoys art, music (especially classical music, jazz, and bluegrass), and reading history. Despite unfounded rumors to the contrary, he never has, and never will, voluntarily bungee jump or sky dive

    ÀúÀÚ : David E. Clough

    ¸ñÂ÷

    1 Mathematical Modeling, Numerical Methods, and Problem Solving
    2 Python Fundamentals
    3 Programming in Python
    4 Roundoff and Truncation Errors
    5 Roots: Bracketing Methods
    6 Roots: Open Methods
    7 Optimization
    8 Linear Algebraic Equations and Matrices
    9 Gauss Elimination
    10 LU Factorization
    11 Matrix Inverse and Condition
    12 Iterative Methods
    13 Eigenvalues
    14 Straight-Line Linear Regression
    15 General Linear and Nonlinear Regression
    16 Fourier Analysis
    17 Polynomial Interpolation
    18 Splines and Piecewise Interpolation
    19 Numerical Integration Formulas
    20 Numerical Integration of Functions
    21 Numerical Differentiation
    22 Initial-Value Problems
    23 Adaptive Methods and Stiff Systems
    24 Boundary-Value Problems

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