Bergepanzerwagen: Bergepanzer 38 to Bergepanther by Thomas L.; Hilary Louis Doyle Jentz

By Thomas L.; Hilary Louis Doyle Jentz

Provided for the 1st time in any book is the attention-grabbing heritage of the Bergepanzerwagen established exclusively on unique records. those absolutely tracked armored restoration cars have been built because the German Panzers turned heavier and tougher to recuperate. contains infrequent pictures and exact 1:35 scale multiview drawings illustrate types of the Bergepanzer 38, the Bergepanzer III, the Bergepanzer IV, the Berge-Panzer VI, and types of the Bergepanther (Ausf.D and Ausf.G)

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Sometimes, as with most of the examples in this book, the observation is more complicated, perhaps taking the form of dissatisfaction with existing theoretical explanations of some complex phenomenon. The issue then becomes how we can fashion existing theoretical ideas and novel hypotheses into a more satistying explanation. Obviously, theory development cannot occur in a vacuum. One needs a solid grasp of existing substantive knowledge and theory about the research domain. Too often, researchers become committed to particular analytic tools, such as computational modeling, and lose sight of the substantive questions.

OR (2) Taber, C. , & Timpone, R. J. (1996) Computational Modeling (Sage University Paper series on Quantitative Applications in the Social Sciences, series no. 07-113). Thousand Oaks, CA: Sage. Page iii Contents Acknowledgments v Series Editor's Introduction vii 1. Introduction 1 Beyond Platforms and On-Ramps 1 Models and Computational Models 2 Why Model Computationally? 3 Where Is Computational Modeling Likely to Be Most Useful? 8 Drawbacks of Computational Modeling 11 General Stages in a Computational Modeling Project 13 An Overview of the Following Chapters 17 2.

Ideally, each cycle through these analytic stages will provide additional understanding, as our theories become richer and our models more precise. , Abelson & Carroll, 1965; McPhee, 1963). Over the past two decades, at an accelerating pace, the tools of computational modeling have become more sophisticated and diverse. Chapters 2 through 4 provide an overview of current methods, from traditional computer simulation through the more recent developments in cognitive science and machine learning.

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