Measuring uncertainty within the theory of evidence. (2018)
- Record Type:
- Book
- Title:
- Measuring uncertainty within the theory of evidence. (2018)
- Main Title:
- Measuring uncertainty within the theory of evidence
- Further Information:
- Note: Simona Salicone, Marco Prioli.
- Authors:
- Salicone, Simona
Prioli, Marco - Contents:
- Intro; Preface; Contents; 1 Introduction; Part I The Background of Measurement Uncertainty; 2 Measurements; 2.1 The Theory of Error; 2.2 The Theory of Uncertainty; 3 Mathematical Methods to Handle Measurement Uncertainty; 3.1 Handling Measurement Uncertainty Within the Probability Theory; 3.1.1 Fundamental Concepts; 3.1.2 The Recommendations of the GUM; 3.1.3 The Recommendations of the Supplement to the GUM; 3.1.4 The Dispute About the Random and the Systematic Contributions to Uncertainty; 3.2 Handling Measurement Uncertainty Within the Theory of Evidence; 3.2.1 Fundamental Concepts. 3.2.2 The RFV Approach3.3 Final Discussion; 4 A First, Preliminary Example; 4.1 School Work A: Characterization of the Measurement Tapes; 4.2 School Work B: Representation of the Measurement Results; 4.2.1 Case 1B; Solution Given by the GUM Approach; Solution Given by the MC Approach; Solution Given by the RFV Approach; Comparison and Discussion; 4.2.2 Case 2B; Solution Given by the GUM Approach; Solution Given by the MC Approach; Solution Given by the RFV Approach; Comparison and Discussion; Further Considerations; 4.2.3 Case 3B; Solution Given by the GUM and MC Approaches. Solution Given by the RFV ApproachComparison and Discussion; 4.3 School Work C: Combination of the Measurement Results; 4.3.1 Case 1C; Solution Given by the GUM Approach; Solution Given by the MC Approach; Solution Given by the RFV Approach; Comparison and Discussion; 4.3.2 Case 2C; Solution Given by the GUM Approach;Intro; Preface; Contents; 1 Introduction; Part I The Background of Measurement Uncertainty; 2 Measurements; 2.1 The Theory of Error; 2.2 The Theory of Uncertainty; 3 Mathematical Methods to Handle Measurement Uncertainty; 3.1 Handling Measurement Uncertainty Within the Probability Theory; 3.1.1 Fundamental Concepts; 3.1.2 The Recommendations of the GUM; 3.1.3 The Recommendations of the Supplement to the GUM; 3.1.4 The Dispute About the Random and the Systematic Contributions to Uncertainty; 3.2 Handling Measurement Uncertainty Within the Theory of Evidence; 3.2.1 Fundamental Concepts. 3.2.2 The RFV Approach3.3 Final Discussion; 4 A First, Preliminary Example; 4.1 School Work A: Characterization of the Measurement Tapes; 4.2 School Work B: Representation of the Measurement Results; 4.2.1 Case 1B; Solution Given by the GUM Approach; Solution Given by the MC Approach; Solution Given by the RFV Approach; Comparison and Discussion; 4.2.2 Case 2B; Solution Given by the GUM Approach; Solution Given by the MC Approach; Solution Given by the RFV Approach; Comparison and Discussion; Further Considerations; 4.2.3 Case 3B; Solution Given by the GUM and MC Approaches. Solution Given by the RFV ApproachComparison and Discussion; 4.3 School Work C: Combination of the Measurement Results; 4.3.1 Case 1C; Solution Given by the GUM Approach; Solution Given by the MC Approach; Solution Given by the RFV Approach; Comparison and Discussion; 4.3.2 Case 2C; Solution Given by the GUM Approach; Solution Given by the MC Approach; Solution Given by the RFV Approach; Comparison and Discussion; 4.3.3 Case 3C; Solution Given by the GUM Approach; Solution Given by the MC Approach; Solution Given by the RFV Approach; Comparison and Discussion; 4.3.4 Case 4C. Solution Given by the GUM and MC ApproachesSolution Given by the RFV Approach; Comparison and Discussion; 4.3.5 Case 5C; Solution Given by the GUM and MC Approaches; Solution Given by the RFV Approach; Comparison and Discussion; 4.4 Conclusions; 4.5 Mathematical Derivations; 4.5.1 Example of Evaluation of the Convolution Product; 4.5.2 Example of Evaluation of the Coverage Intervals; Part II The Mathematical Theory of Evidence; 5 Introduction: Probability and Belief Functions; 6 Basic Definitions of the Theory of Evidence; 6.1 Mathematical Derivations; 6.1.1 Proof of Theorem 6.1. 6.1.2 Proof of Theorem 6.26.1.3 Proof of Theorem 6.3; 6.1.4 Proof of Theorem 6.4; 6.1.5 Proof of Theorem 6.5; 7 Particular Cases of the Theory of Evidence; 7.1 The Probability Theory; 7.1.1 The Probability Functions; 7.1.2 The Probability Distribution Functions; 7.1.3 The Representation of Knowledge in the Probability Theory; 7.2 The Possibility Theory; 7.2.1 Necessity and Possibility Functions; 7.2.2 The Possibility Distribution Function; 7.2.3 The Representation of Knowledge in the Possibility Theory; 7.3 Comparison Between the Probability and the Possibility Theories. … (more)
- Publisher Details:
- Cham, Switzerland : Springer
- Publication Date:
- 2018
- Extent:
- 1 online resource
- Subjects:
- 003/.54
Mathematics
Measurement uncertainty (Statistics)
Uncertainty (Information theory)
SCIENCE -- System Theory
TECHNOLOGY & ENGINEERING -- Operations Research
Measurement uncertainty (Statistics)
Uncertainty (Information theory)
Distribution (Probability theory)
Mathematics -- Probability & Statistics -- General
Probability & statistics
Electronic books - Languages:
- English
- ISBNs:
- 9783319741390
3319741373
9783319741376 - Related ISBNs:
- 331974139X
9783319741376 - Notes:
- Note: Includes bibliographical references and index.
Note: Online resource; title from PDF title page (SpringerLink, viewed May 1, 2018). - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.367057
- Ingest File:
- 01_342.xml