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One of the major goals of geophysical inversion is to find earth models that explain the geophysical observations. Thus the branch of mathematics known as optimization has found significant use in many geophysical applications.
Both local and global optimization methods are used in the estimation of material properties from geophysical data. As the title of the book suggests, the aim of this book is to describe the application of several recently developed global optimization methods to geophysical problems.
• The well known linear and gradient based optimization methods have been summarized in order to explain their advantages and limitations
• The theory of simulated annealing and genetic algorithms have been described in sufficient detail for the readers to understand the underlying fundamental principles upon which these algorithms are based
• The algorithms have been described using simple flow charts (the algorithms are general and can be applied to a wide variety of problems
Students, researchers and practitioners will be able to design practical algorithms to solve their specific geophysical inversion problems. The book is virtually self-contained so that there are no prerequisites, except for a fundamental mathematical background that includes a basic understanding of linear algebra and calculus
|Ch. 1||Preliminary Statistics||1|
|Ch. 2||Direct, Linear and Iterative-linear Inverse Methods||27|
|Ch. 3||Monte Carlo Methods||67|
|Ch. 4||Simulated Annealing Methods||79|
|Ch. 5||Genetic Algorithms||125|
|Ch. 6||Geophysical Applications of SA and GA||159|
|Ch. 7||Uncertainty Estimation||245|