Computing Statistics Under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering: 393 - Rilegato

Nguyen, Hung T.; Kreinovich, Vladik; Wu, Berlin; Xiang, Gang

Rilegato

ISBN 10: 3642249043 ISBN 13: 9783642249044

Casa editrice: Springer Nature, 2011

Riassunto

In many practical situations, we are interested in statistics characterizing a population of objects: e.g. in the mean height of people from a certain area.

Most algorithms for estimating such statistics assume that the sample values are exact. In practice, sample values come from measurements, and measurements are never absolutely accurate. Sometimes, we know the exact probability distribution of the measurement inaccuracy, but often, we only know the upper bound on this inaccuracy. In this case, we have interval uncertainty: e.g. if the measured value is 1.0, and inaccuracy is bounded by 0.1, then the actual (unknown) value of the quantity can be anywhere between 1.0 - 0.1 = 0.9 and 1.0 + 0.1 = 1.1. In other cases, the values are expert estimates, and we only have fuzzy information about the estimation inaccuracy.

This book shows how to compute statistics under such interval and fuzzy uncertainty. The resulting methods are applied to computer science (optimal scheduling of different processors), to information technology (maintaining privacy), to computer engineering (design of computer chips), and to data processing in geosciences, radar imaging, and structural mechanics.

Su questo libro

Recensione

From the reviews:

“This book is a research exposition by Kreinovich and coworkers. ... The main goal is to present algorithms for computation of statistical characteristics (like variance) but under interval and fuzzy uncertainty of the available data. In this book, fuzzy uncertainty is reduced to interval uncertainty by alpha-cutwise consideration of (convex) fuzzy uncertainty. ... For increase of readability, mathematical proofs are presented always at the end of the chapters.” (Wolfgang Näther, Zentralblatt MATH, Vol. 1238, 2012)

Contenuti

Part I Computing Statistics under Interval and Fuzzy Uncertainty: Formulation of the Problem and an Overview of General Techniques Which Can Be Used for Solving this Problem.- Part II Algorithms for Computing Statistics Under Interval and Fuzzy Uncertainty.- Part III Towards Computing Statistics under Interval and Fuzzy Uncertainty: Gauging the Quality of the Input Data.- Part IV Applications.- Part V Beyond Interval and Fuzzy Uncertainty.

Dettagli dell?edizione

• Editore: Springer Nature
• Data di pubblicazione: 2011
• ISBN 10: 3642249043
• ISBN 13: 9783642249044
• Rilegatura: Copertina rigida
• Lingua: Inglese
• Numero di pagine: 430