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ISBN: 9783790815429
In probability and statistics we often have to estimate probabilities and parameters in probability distributions using a random sample. Instead of using a point estimate calculated from … Mehr…
ISBN: 379081542X
[EAN: 9783790815429], Neubuch, Mathematics|Logic, Mathematics|Probability & Statistics, Mathematics|Probability & Statistics|General, Mathematics|Set Theory, Computers & the Internet|Data… Mehr…
ISBN: 379081542X
[EAN: 9783790815429], Gebraucht, guter Zustand, Mathematics|Logic, Mathematics|Probability & Statistics, Mathematics|Probability & Statistics|General, Mathematics|Set Theory, Computers & … Mehr…
ISBN: 9783790815429
Used - Good. Former Library book. Shows some signs of wear, and may have some markings on the inside., 2.5
2003, ISBN: 379081542X
[EAN: 9783790815429], Neubuch, [PU: Physica]
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Detailangaben zum Buch - Fuzzy Probabilities
EAN (ISBN-13): 9783790815429
ISBN (ISBN-10): 379081542X
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2003
Herausgeber: Physica
Buch in der Datenbank seit 2008-12-22T20:15:47+01:00 (Berlin)
Detailseite zuletzt geändert am 2021-06-05T19:38:42+02:00 (Berlin)
ISBN/EAN: 379081542X
ISBN - alternative Schreibweisen:
3-7908-1542-X, 978-3-7908-1542-9
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: gustav klimt
Titel des Buches: fuzzy probabilities, fuzzy probability
Daten vom Verlag:
Autor/in: James J. Buckley
Titel: Studies in Fuzziness and Soft Computing; Fuzzy Probabilities - New Approach and Applications
Verlag: Physica; Physica
165 Seiten
Erscheinungsjahr: 2002-11-26
Heidelberg; DE
Gewicht: 0,380 kg
Sprache: Englisch
85,55 € (DE)
87,95 € (AT)
106,60 CHF (CH)
Not available, publisher indicates OP
BB; Book; Hardcover, Softcover / Informatik, EDV/Anwendungs-Software; Künstliche Intelligenz; Verstehen; fuzzy numbers; decision model; probability theory; decision problem; fuzzy parameters; decision theory; Extension; control; fuzzy sets; uncertain probabilities; fuzzy probability theory; C; Artificial Intelligence (incl. Robotics); Engineering; Robotik; BC; EA
1 Introduction.- 1.1 Introduction.- 1.2 References.- 2 Fuzzy Sets.- 2.1 Introduction.- 2.2 Fuzzy Sets.- 2.2.1 Fuzzy Numbers.- 2.2.2 Alpha-Cuts.- 2.2.3 Inequalities.- 2.2.4 Discrete Fuzzy Sets.- 2.3 Fuzzy Arithmetic.- 2.3.1 Extension Principle.- 2.3.2 Interval Arithmetic.- 2.3.3 Fuzzy Arithmetic.- 2.4 Fuzzy Functions.- 2.4.1 Extension Principle.- 2.4.2 Alpha-Cuts and Interval Arithmetic.- 2.4.3 Differences.- 2.5 Finding the Minimum of a Fuzzy Number.- 2.6 Ordering Fuzzy Numbers.- 2.7 Fuzzy Probabilities.- 2.8 Fuzzy Numbers from Confidence Intervals.- 2.9 Computing Fuzzy Probabilities.- 2.9.1 First Problem.- 2.9.2 Second Problem.- 2.10 Figures.- 2.11 References.- 3 Fuzzy Probability Theory.- 3.1 Introduction.- 3.2 Fuzzy Probability.- 3.3 Fuzzy Conditional Probability.- 3.4 Fuzzy Independence.- 3.5 Fuzzy Bayes’ Formula.- 3.6 Applications.- 3.6.1 Blood Types.- 3.6.2 Resistance to Surveys.- 3.6.3 Testing for HIV.- 3.6.4 Color Blindness.- 3.6.5 Fuzzy Bayes.- 3.7 References.- 4 Discrete Fuzzy Random Variables.- 4.1 Introduction.- 4.2 Fuzzy Binomial.- 4.3 Fuzzy Poisson.- 4.4 Applications.- 4.4.1 Fuzzy Poisson Approximating Fuzzy Binomial.- 4.4.2 Overbooking.- 4.4.3 Rapid Response Team.- 4.5 References.- 5 Fuzzy Queuing Theory.- 5.1 Introduction.- 5.2 Regular, Finite, Markov Chains.- 5.3 Fuzzy Queuing Theory.- 5.4 Applications.- 5.4.1 Machine Servicing Problem.- 5.4.2 Fuzzy Queuing Decision Problem.- 5.5 References.- 6 Fuzzy Markov Chains.- 6.1 Introduction.- 6.2 Regular Markov Chains.- 6.3 Absorbing Markov Chains.- 6.4 Application: Decision Model.- 6.5 References.- 7 Fuzzy Decisions Under Risk.- 7.1 Introduction.- 7.2 Without Data.- 7.3 With Data.- 7.4 References.- 8 Continuous Fuzzy Random Variables.- 8.1 Introduction.- 8.2 Fuzzy Uniform.- 8.3 Fuzzy Normal.- 8.4 Fuzzy Negative Exponential.- 8.5 Applications.- 8.5.1 Fuzzy Uniform.- 8.5.2 Fuzzy Normal Approximation to Fuzzy Binomial.- 8.5.3 Fuzzy Normal Approximation to Fuzzy Poisson.- 8.5.4 Fuzzy Normal.- 8.5.5 Fuzzy Negative Exponential.- 8.6 References.- 9 Fuzzy Inventory Control.- 9.1 Introduction.- 9.2 Single Period Model.- 9.3 Multiple Periods.- 9.4 References.- 10 Joint Fuzzy Probability Distributions.- 10.1 Introduction.- 10.2 Continuous Case.- 10.2.1 Fuzzy Marginals.- 10.2.2 Fuzzy Conditionals.- 10.2.3 Fuzzy Correlation.- 10.2.4 Fuzzy Bivariate Normal.- 10.3 References.- 11 Applications of Joint Distributions.- 11.1 Introduction.- 11.2 Political Polls.- 11.2.1 Fuzzy Marginals.- 11.2.2 Fuzzy Conditionals.- 11.2.3 Fuzzy Correlation.- 11.3 Fuzzy Reliability Theory.- 11.4 References.- 12 Functions of a Fuzzy Random Variable.- 12.1 Introduction.- 12.2 Discrete Fuzzy Random Variables.- 12.3 Continuous Fuzzy Random Variables.- 13 Functions of Fuzzy Random Variables.- 13.1 Introduction.- 13.2 One-to-One Transformation.- 13.3 Other Transformations.- 14 Law of Large Numbers.- 15 Sums of Fuzzy Random Variables.- 15.1 Introduction.- 15.2 Sums.- 16 Conclusions and Future Research.- 16.1 Introduction.- 16.2 Summary.- 16.2.1 Chapter 3.- 16.2.2 Chapter 4.- 16.2.3 Chapter 5.- 16.2.4 Chapter 6.- 16.2.5 Chapter 7.- 16.2.6 Chapter 8.- 16.2.7 Chapter 9.- 16.2.8 Chapter 10.- 16.2.9 Chapter 11.- 16.2.10 Chapter 12.- 16.2.11 Chapter 13.- 16.2.12 Chapter 14.- 16.2.13 Chapter 15.- 16.3 Research Agenda.- 16.3.1 Chapter 3.- 16.3.2 Chapter 4.- 16.3.3 Chapter 5.- 16.3.4 Chapter 6.- 16.3.5 Chapter 7.- 16.3.6 Chapter 8.- 16.3.7 Chapter 9.- 16.3.8 Chapter 10.- 16.3.9 Chapter 11.- 16.3.10 Chapter 12.- 16.3.11 Chapter 13.- 16.3.12 Chapter 14.- 16.3.13 Chapter 15.- 16.4 Conclusions.- List of Figures.- List of Tables.New method of dealing with imprecise probabilities, most of which not published before
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