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Engineering - Computational Intelligence and Complexity | Mathematical Modeling

Mathematical Modeling

Heinz, Stefan

2011, XVI, 460 p.

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  • Covers the complete range of analytical and simulation modeling, spanning deterministic and stochastic methodologies
  • Demonstrating how complete solutions for modeling problems can be obtained
  • Offers homework problems after chapter subsections and an Instructor’s  homework solution manual

The whole picture of Mathematical Modeling is systematically and thoroughly explained in this text for undergraduate and graduate students of mathematics, engineering, economics, finance, biology, chemistry, and physics. This textbook gives an overview of the spectrum of modeling techniques, deterministic and stochastic methods, and first-principle and empirical solutions.

Complete range: The text continuously covers the complete range of basic modeling techniques: it provides a consistent transition from simple algebraic analysis methods to simulation methods used for research. Such an overview of the spectrum of modeling techniques is very helpful for the understanding of how a research problem considered can be appropriately addressed.

Complete methods: Real-world processes always involve uncertainty, and the consideration of randomness is often relevant. Many students know deterministic methods, but they do hardly have access to stochastic methods, which are described in advanced textbooks on probability theory. The book develops consistently both deterministic and stochastic methods. In particular, it shows how deterministic methods are generalized by stochastic methods.

Complete solutions: A variety of empirical approximations is often available for the modeling of processes. The question of which assumption is valid under certain conditions is clearly relevant. The book provides a bridge between empirical modeling and first-principle methods: it explains how the principles of modeling can be used to explain the validity of empirical assumptions. The basic features of micro-scale and macro-scale modeling are discussed – which is an important problem of current research.

Content Level » Upper undergraduate

Related subjects » Chemistry - Computational Intelligence and Complexity - Mathematics - Theoretical, Mathematical & Computational Physics

Table of contents 

Deterministic Analysis of Observations.-Stochastic Analysis of Observations.-Deterministic States.-Stochastic States.-Deterministic Changes.-Stochastic Changes.-Deterministic Evolution.-Stochastic Evolution.-Deterministic Multivariate Evolution.-Stochastic Multivariate Evolution."

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