Księgarnia naukowa
English Polski
Dostęp on-line

Książki

0.00 PLN
Schowek (0) 
Schowek jest pusty
Data Uncertainty and Important Measures

Data Uncertainty and Important Measures

Autorzy
Wydawnictwo ISTE Publishing Company
Data wydania 01/01/2018
Wydanie Pierwsze
Liczba stron 250
Forma publikacji książka w twardej oprawie
Poziom zaawansowania Dla profesjonalistów, specjalistów i badaczy naukowych
Język angielski
ISBN 9781848219939
Kategorie modelowanie matematyczne
639.29 PLN (z VAT)
$166.45 / €149.40 / £128.63 /
Produkt na zamówienie
Przesyłka w 5-6 tygodni
Ilość
Do schowka

Opis książki

The first part of the book defines the concept of uncertainties and the mathematical frameworks that will be used for uncertainty modeling. The application to system reliability assessment illustrates the concept. In the second part, evidential networks as a new tool to model uncertainty in reliability and risk analysis is proposed and described. Then it is applied on SIS performance assessment and in risk analysis of a heat sink. In the third part, Bayesian and evidential networks are used to deal with important measures evaluation in the context of uncertainties.

Data Uncertainty and Important Measures

Spis treści

Foreword xi


Acknowledgments xiii


Chapter 1. Why and Where Uncertainties 1


1.1. Sources and forms of uncertainty 1


1.2. Types of uncertainty 3


1.3. Sources of uncertainty 3


1.4. Conclusion 6


Chapter 2. Models and Language of Uncertainty 9


2.1. Introduction 9


2.2. Probability theory 11


2.2.1. Interpretations 11


2.2.2. Fundamental notions 13


2.2.3. Discussion 15


2.3. Belief functions theory 15


2.3.1. Representation of beliefs 16


2.3.2. Combination rules 18


2.3.3. Extension and marginalization 20


2.3.4. Pignistic transformation 20


2.3.5. Discussion 21


2.4. Fuzzy set theory 21


2.4.1. Basic definitions 22


2.4.2. Operations on fuzzy sets 22


2.4.3. Fuzzy relations 23


2.5. Fuzzy arithmetic 25


2.5.1. Fuzzy numbers 26


2.5.2. Fuzzy probabilities 28


2.5.3. Discussion 29


2.6. Possibility theory 29


2.6.1. Definitions 30


2.6.2. Possibility and necessity measures 30


2.6.3. Operations on possibility and necessity measures 32


2.7. Random set theory 32


2.7.1. Basic definitions 33


2.7.2. Expectation of random sets 34


2.7.3. Random intervals 35


2.7.4. Confidence interval 35


2.7.5. Discussion 36


2.8. Confidence structures or c-boxes 36


2.8.1. Basic notions 36


2.8.2. Confidence distributions 37


2.8.3. P-boxes and C-boxes 38


2.8.4. Discussion 40


2.9. Imprecise probability theory 40


2.9.1. Definitions 41


2.9.2. Basic properties 42


2.9.3. Discussion 44


2.10. Conclusion 44


Chapter 3. Risk Graphs and Risk Matrices: Application of Fuzzy Sets and Belief Reasoning 47


3.1. SIL allocation scheme 48


3.1.1. Safety instrumented systems (SIS) 48


3.1.2. Conformity to standards ANSI/ISA S84.01-1996 and IEC 61508 49


3.1.3. Taxonomy of risk/SIL assessment methods 50


3.1.4. Risk assessment 50


3.1.5. SIL allocation process 52


3.1.6. The use of experts' opinions 53


3.2. SIL allocation based on possibility theory 54


3.2.1. Eliciting the experts' opinions 54


3.2.2. Rating scales for parameters 55


3.2.3. Subjective elicitation of the risk parameters 56


3.2.4. Calibration of experts' opinions 59


3.2.5. Aggregation of the opinions 61


3.3. Fuzzy risk graph 65


3.3.1. Input fuzzy partition and fuzzification 65


3.3.2. Risk/SIL graph logic by fuzzy inference system 66


3.3.3. Output fuzzy partition and defuzzification 67


3.3.4. Illustration case 69


3.4. Risk/SIL graph: belief functions reasoning 72


3.4.1. Elicitation of expert opinions in the belief functions theory 72


3.4.2. Aggregation of expert opinions 73


3.5. Evidential risk gra

Polecamy również książki

Strony www Białystok Warszawa
801 777 223