Contents

**Preface XI**

	- Vladimir Artemyev, Jury Rudenko and George Nistratov

#### **X** Contents


Preface

One can't embrace the unembraceable

Truth is what stands the test of experience… The significant problems we have can't be solved

at the same level of thinking with which we created them

Today there are always situations when results of tests and experience cannot solve system engineering problems "at the same level of thinking with which we created them." These tests and our experience may be incapable of predicting the "truth." This is a consequence of high complexity and uncertainty. In these conditions, probabilistic models are quite often

In this book, various sets of original and traditional models applicable to different systems are presented. The content is structured in sections: General Propositions for Solving Ana‐ lytical Problems (two chapters), Modeling of Industrial Systems (three chapters), Modeling of Natural Hazards (one chapter), Modeling of Automotive Equipment and Systems (one chapter), Modeling of Transport and Cosmic Systems (two chapters), Modeling for Informa‐ tion Security (two chapters), and Modeling for Systems Protection Against Terrorist Threats (one chapter). This means that the application area of the presented models is wide enough, and dozens of practical examples confirm achievable effects. Certainly, the illustrated practi‐ cal possibilities of probabilistic modeling cannot cover the huge set of problems in system engineering. Nevertheless, in searching for the "truth" the presented chapters estimate the

The purposes of this text are to enrich your knowledge of probabilistic modeling and to ex‐

The first idea for reader to understand is the time of innovations in probabilistic modeling, and not to be late with their implementations at levels of system engineering. Today, system engineering is an interdisciplinary approach governing the total technical and managerial effort required for transforming a set of stakeholder needs, expectations, and constraints in‐ to a solution and to support that solution throughout its life. Therefore, each engineer should know about the possibilities of probabilistic models for researching system operation in changing conditions and threats. For the wary reader, who expects the proposed ap‐ proaches "to embrace the unembraceable" under the pretext of the coming globalization, we can say "Do not worry—you are not late yet." However, please do not hesitate to pay atten‐

wonderful possibilities of probabilistic modeling from different points of view.

pand the application borders for solving modern system engineering problems.

applied to predict and estimate defined results.

Two basic ideas define the concept of this book.

*Kozma Prutkov, 1854*

*Albert Einstein, 1879–1955*
