Computing Statistics under Interval and Fuzzy Uncertainty : Applications to Computer Science and Engineering
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...
সংরক্ষণ করুন:
| প্রধান লেখক: | , , , |
|---|---|
| বিন্যাস: | Livre numérique |
| ভাষা: | Anglais |
| প্রকাশিত: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| সংস্করন: | 1st ed. 2012. |
| মালা: | Studies in Computational Intelligence
393 |
| অনলাইন ব্যবহার করুন: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| টীকা: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Computing Statistics under Interval and Fuzzy Uncertainty, Texte imprimé, 9783642249044 • Computing Statistics under Interval and Fuzzy Uncertainty, Texte imprimé, 9783642445705 • Computing Statistics under Interval and Fuzzy Uncertainty, Texte imprimé, 9783642249044 • Computing Statistics under Interval and Fuzzy Uncertainty, Texte imprimé, 9783642249068 |
| সংক্ষিপ্ত: | 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 |
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| উপাদানের বিবরণ: | Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| আইসবিএন: | 9783642249051 |
| আইএসএসএন: | 1860-9503 |
| প্রবেশাধিকার: | Accès en ligne pour les établissements français bénéficiaires des licences nationales Accès soumis à abonnement pour tout autre établissement Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 |