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سعر ومواصفات Generic Modelling Under Risk And Uncertainty: An Introduction To Statistical, Phenomenological And Computational Methods By Etienne De Rocquigny

  • أفضل سعر لـ Generic Modelling Under Risk And Uncertainty: An Introduction To Statistical, Phenomenological And Computational Methods By Etienne De Rocquigny by جوميا فى مصر هو 1,403 ج.م.
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  • أول ظهور لهذا المنتج كان فى ديسمبر 29, 2017

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  • Category Type‎:‎ Mathematics
  • ISBN‎:‎ 9780470695142
  • Author‎:‎ Etienne de Rocquigny
  • Publisher‎:‎ John Wiley & Sons
  • Binding‎:‎ Paperback
  • Book Language‎:‎ English

Modelling has permeated virtually all areas of industrial‎,‎ environmental‎,‎ economic‎,‎ bio‎-medical or civil engineering‎:‎ yet the use of models for decision‎-making raises a number of issues to which this book is dedicated‎:‎ How uncertain is my model ‎?‎ Is it truly valuable to support decision‎-making ‎?‎ What kind of decision can be truly supported and how can I handle residual uncertainty ‎?‎ How much refined should the mathematical description be‎,‎ given the true data limitations ‎?‎ Could the uncertainty be reduced through more data‎,‎ increased modeling investment or computational budget ‎?‎ Should it be reduced now or later ‎?‎ How robust is the analysis or the computational methods involved ‎?‎ Should / could those methods be more robust ‎?‎ Does it make sense to handle uncertainty‎,‎ risk‎,‎ lack of knowledge‎,‎ variability or errors altogether ‎?‎ How reasonable is the choice of probabilistic modeling for rare events ‎?‎ How rare are the events to be considered ‎?‎ How far does it make sense to handle extreme events and elaborate confidence figures ‎?‎ Can I take advantage of expert / phenomenological knowledge to tighten the probabilistic figures ‎?‎Are there connex domains that could provide models or inspiration for my problem ‎?‎ Written by a leader at the crossroads of industry‎,‎ academia and engineering‎,‎ and based on decades of multi‎-disciplinary field experience‎,‎ Modelling Under Risk and Uncertainty gives a self‎-consistent introduction to the methods involved by any type of modeling development acknowledging the inevitable uncertainty and associated risks‎.‎ It goes beyond the black‎-box view that some analysts‎,‎ modelers‎,‎ risk experts or statisticians develop on the underlying phenomenology of the environmental or industrial processes‎,‎ without valuing enough their physical properties and inner modelling potential nor challenging the practical plausibility of mathematical hypotheses‎;‎ conversely it is also to attract environmental or engineering modellers to better handle model confidence issues through finer statistical and risk analysis material taking advantage of advanced scientific computing‎,‎ to face new regulations departing from deterministic design or support robust decision‎-making‎.‎Modelling Under Risk and Uncertainty‎:‎ * Addresses a concern of growing interest for large industries‎,‎ environmentalists or analysts‎:‎ robust modeling for decision‎-making in complex systems‎.‎ * Gives new insights into the peculiar mathematical and computational challenges generated by recent industrial safety or environmental control analysis for rare events‎.‎ * Implements decision theory choices differentiating or aggregating the dimensions of risk/aleatory and epistemic uncertainty through a consistent multi‎-disciplinary set of statistical estimation‎,‎ physical modelling‎,‎ robust computation and risk analysis‎.‎ * Provides an original review of the advanced inverse probabilistic approaches for model identification‎,‎ calibration or data assimilation‎,‎ key to digest fast‎-growing multi‎-physical data acquisition‎.‎ * Illustrated with one favourite pedagogical example crossing natural risk‎,‎ engineering and economics‎,‎ developed throughout the book to facilitate the reading and understanding‎.‎* Supports Master/PhD‎-level course as well as advanced tutorials for professional training Analysts and researchers in numerical modeling‎,‎ applied statistics‎,‎ scientific computing‎,‎ reliability‎,‎ advanced engineering‎,‎ natural risk or environmental science will benefit from this book‎.‎

  • Author‎:‎ Etienne de Rocquigny
  • Publisher‎:‎ John Wiley & Sons
  • ISBN‎:‎ 9780470695142

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