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Titlebook: Uncertainty and Sensitivity Analysis in Archaeological Computational Modeling; Marieka Brouwer Burg,Hans Peeters,William A. Lovis Book 201

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書(shū)目名稱Uncertainty and Sensitivity Analysis in Archaeological Computational Modeling
編輯Marieka Brouwer Burg,Hans Peeters,William A. Lovis
視頻videohttp://file.papertrans.cn/942/941128/941128.mp4
概述Addresses the critical yet almost completely under-problematized and under-theorized issue of uncertainty in archaeological modeling, as well as methods for model validation.Includes contributions by
叢書(shū)名稱Interdisciplinary Contributions to Archaeology
圖書(shū)封面Titlebook: Uncertainty and Sensitivity Analysis in Archaeological Computational Modeling;  Marieka Brouwer Burg,Hans Peeters,William A. Lovis Book 201
描述.Thisvolume deals with the pressing issue of uncertainty in archaeological modeling.Detecting where and when uncertainty is introduced to the modeling process iscritical, as are strategies for minimizing, reconciling, or accommodating suchuncertainty. Included chapters provide unique perspectives on uncertainty inarchaeological modeling, ranging in both theoretical and methodologicalorientation. The strengths and weaknesses of various identification andmitigation techniques are discussed, in particular sensitivity analysis. Thechapters demonstrate that for archaeological modeling purposes, there is noquick fix for uncertainty; indeed, each archaeological model requires intensiveconsideration of uncertainty and specific applications for calibration andvalidation. As very few such techniques have been problematized in a systematicmanner or published in the archaeological literature, this volume aims toprovide guidance and direction to other modelers in the field by distillingsome basic principles for model testing derived from insight gathered in thecase studies presented. Additionally, model applications and their attendantuncertainties are presented from distinct spatio-temporal co
出版日期Book 2016
關(guān)鍵詞Agent based modeling (ABM); Differential criteria weighting; Empirical data set mining and inductive p
版次1
doihttps://doi.org/10.1007/978-3-319-27833-9
isbn_softcover978-3-319-80225-1
isbn_ebook978-3-319-27833-9Series ISSN 1568-2722 Series E-ISSN 2730-6984
issn_series 1568-2722
copyrightSpringer International Publishing Switzerland 2016
The information of publication is updating

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Epistemic Considerations About Uncertainty and Model Selection in Computational Archaeology: A Caseerent goals (prediction, reconstruction, and exploration). Whatever the focus of any particular model, however, we have to deal with aspects of uncertainty, which are not easily tackled. The uncertainty relates to the very nature of archaeological datasets as well as to the model itself, and both ty
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Assessing Nonlinear Behaviors in an Agent-Based Model,lating to cultural transmission in small-scale societies. Sensitivity analysis revealed disproportionate or nonlinear relationships between parameter changes and model behaviors. Nonlinear sensitivity may indicate underlying problems in programming or model design; however, it may also reveal unanti
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Scale Dependency in Agent-Based Modeling: How Many Time Steps? How Many Simulations? How Many Agentisions about how long to run a simulation to generate patterns of interest, or how many simulations are necessary to capture the range of patterns generated by a stochastic model, are an important part of the design and testing process. In archaeological agent-based modeling (ABM), though, researche
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Archaeological Simulation and the Testing Paradigm,omputational approaches (such as agent-based modeling and multi-agent simulation), evaluative statistical tools (such as sensitivity or uncertainty analyses), and borrow heavily from similar applications in other disciplines; particularly ones that emphasize the dynamic (or dynamical) group behavior
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