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A Novel Decision Probability Transformation Method Based On Belief Interval


A Novel Decision Probability Transformation Method Based On Belief Interval
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A Novel Decision Probability Transformation Method Based On Belief Interval


A Novel Decision Probability Transformation Method Based On Belief Interval
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Author : Zhan Deng
language : en
Publisher: Infinite Study
Release Date :

A Novel Decision Probability Transformation Method Based On Belief Interval written by Zhan Deng and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Education categories.


In Dempster–Shafer evidence theory, the basic probability assignment (BPA) can effectively represent and process uncertain information. How to transform the BPA of uncertain information into a decision probability remains a problem to be solved. In the light of this issue, we develop a novel decision probability transformation method to realize the transition from the belief decision to the probability decision in the framework of Dempster–Shafer evidence theory. The newly proposed method considers the transformation of BPA with multi-subset focal elements from the perspective of the belief interval, and applies the continuous interval argument ordered weighted average operator to quantify the data information contained in the belief interval for each singleton. Afterward, we present an approach to calculate the support degree of the singleton based on quantitative data information. According to the support degree of the singleton, the BPA of multi-subset focal elements is allocated reasonably. Furthermore, we introduce the concepts of probabilistic information content in this paper, which is utilized to evaluate the performance of the decision probability transformation method. Eventually, a few numerical examples and a practical application are given to demonstrate the rationality and accuracy of our proposed method.



Belief Interval Based Distance Measures In The Theory Of Belief Functions


Belief Interval Based Distance Measures In The Theory Of Belief Functions
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Author : Deqiang Han
language : en
Publisher: Infinite Study
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Belief Interval Based Distance Measures In The Theory Of Belief Functions written by Deqiang Han and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Education categories.


In belief functions related fields, the distance measure is an important concept, which represents the degree of dissimilarity between bodies of evidence. Various distance measures of evidence have been proposed and widely used in diverse belief function related applications, especially in performance evaluation. Existing definitions of strict and nonstrict distance measures of evidence have their own pros and cons. In this paper, we propose two new strict distance measures of evidence (Euclidean and Chebyshev forms) between two basic belief assignments based on the Wasserstein distance between belief intervals of focal elements. Illustrative examples, simulations, applications, and related analyses are provided to show the rationality and efficiency of our proposed measures for distance of evidence.



Advances And Applications Of Dsmt For Information Fusion Vol Iv


Advances And Applications Of Dsmt For Information Fusion Vol Iv
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Author : Florentin Smarandache, Jean Dezert
language : en
Publisher: Infinite Study
Release Date : 2015-03-01

Advances And Applications Of Dsmt For Information Fusion Vol Iv written by Florentin Smarandache, Jean Dezert and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-01 with categories.


The fourth volume on Advances and Applications of Dezert-Smarandache Theory (DSmT) for information fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics. The contributions (see List of Articles published in this book, at the end of the volume) have been published or presented after disseminating the third volume (2009, http://fs.gallup.unm.edu/DSmT-book3.pdf) ininternational conferences, seminars, workshops and journals.



Advances And Applications Of Dsmt For Information Fusion Collected Works Volume 4


Advances And Applications Of Dsmt For Information Fusion Collected Works Volume 4
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Author : Florentin Smarandache
language : en
Publisher: Infinite Study
Release Date : 2015-07-01

Advances And Applications Of Dsmt For Information Fusion Collected Works Volume 4 written by Florentin Smarandache and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-01 with Mathematics categories.


The fourth volume on Advances and Applications of Dezert-Smarandache Theory (DSmT) for information fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics. The contributions have been published or presented after disseminating the third volume (2009, http://fs.gallup.unm.edu/DSmT-book3.pdf) in international conferences, seminars, workshops and journals.



Advances And Applications Of Dsmt For Information Fusion Collected Works Volume 5


Advances And Applications Of Dsmt For Information Fusion Collected Works Volume 5
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Author : Florentin Smarandache
language : en
Publisher: Infinite Study
Release Date :

Advances And Applications Of Dsmt For Information Fusion Collected Works Volume 5 written by Florentin Smarandache and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.


This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 (available at fs.unm.edu/DSmT-book4.pdf or www.onera.fr/sites/default/files/297/2015-DSmT-Book4.pdf) in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well.



Machine Learning For Cyber Security


Machine Learning For Cyber Security
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Author : Yuan Xu
language : en
Publisher: Springer Nature
Release Date : 2023-01-12

Machine Learning For Cyber Security written by Yuan Xu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-12 with Computers categories.


The three-volume proceedings set LNCS 13655,13656 and 13657 constitutes the refereedproceedings of the 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, which taking place during December 2–4, 2022, held in Guangzhou, China. The 100 full papers and 46 short papers were included in these proceedings were carefully reviewed and selected from 367 submissions.



Interval Probabilistic Uncertainty And Non Classical Logics


Interval Probabilistic Uncertainty And Non Classical Logics
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Author : Van-Nam Huynh
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-01-11

Interval Probabilistic Uncertainty And Non Classical Logics written by Van-Nam Huynh and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-01-11 with Mathematics categories.


This book contains the proceedings of the first International Workshop on Interval/Probabilistic Uncertainty and Non Classical Logics, Ishikawa, Japan, March 25-28, 2008. The workshop brought together researchers working on interval and probabilistic uncertainty and on non-classical logics. It is hoped this workshop will lead to a boost in the much-needed collaboration between the uncertainty analysis and non-classical logic communities, and thus, to better processing of uncertainty.



Technologies For Constructing Intelligent Systems 1


Technologies For Constructing Intelligent Systems 1
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Author : Bernadette Bouchon-Meunier
language : en
Publisher: Physica
Release Date : 2013-03-20

Technologies For Constructing Intelligent Systems 1 written by Bernadette Bouchon-Meunier and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-20 with Computers categories.


Intelligent systems enhance the capacities made available by the internet and other computer-based technologies. This book deals with the theory behind the solutions to difficult problems in the construction of intelligent systems. Particular attention is paid to situations in which the available information and data may be imprecise, uncertain, incomplete or of linguistic nature. Various methodologies for these cases are discussed, among which are probabilistic, possibilistic, fuzzy, logical, evidential and network-based frameworks. One purpose of the book is to consider how these methods can be used cooperatively. Topics included in the book include fundamental issues in uncertainty, the rapidly emerging discipline of information aggregation, neural networks, bayesian networks and other network methods, as well as logic-based systems.



A New Probabilistic Transformation Based On Evolutionary Algorithm For Decision Making


A New Probabilistic Transformation Based On Evolutionary Algorithm For Decision Making
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Author : Yilin Dong
language : un
Publisher: Infinite Study
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A New Probabilistic Transformation Based On Evolutionary Algorithm For Decision Making written by Yilin Dong and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.


The study of alternative probabilistic transformation (PT) in DS theory has emerged recently as an interesting topic, especially in decision making applications. These recent studies have mainly focused on investigating various schemes for assigning both the mass of compound focal elements to each singleton in order to obtain Bayesian belief function for realworld decision making problems. In this paper, work by us also takes inspiration from both Bayesian transformation camps, with a novel evolutionary-based probabilistic transformation (EPT) to select the qualified Bayesian belief function with the maximum value of probabilistic information content (PIC) benefiting from the global optimizing capabilities of evolutionary algorithms. Verification of EPT is carried out by testing it on a set of numerical examples on 4D frames. On each problem instance, comparisons are made between the novel method and those existing approaches, which illustrate the superiority of the proposed method in this paper. Moreover, a simple constraint-handling strategy with EPT is proposed to tackle target type tracking (TTT) problem, simulation results of the constrained EPT on TTT problem prove the rationality of this modification.



Advancements In Fuzzy Reliability Theory


Advancements In Fuzzy Reliability Theory
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Author : Kumar, Akshay
language : en
Publisher: IGI Global
Release Date : 2021-02-12

Advancements In Fuzzy Reliability Theory written by Kumar, Akshay and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-12 with Mathematics categories.


In recent years, substantial efforts are being made in the development of reliability theory including fuzzy reliability theories and their applications to various real-life problems. Fuzzy set theory is widely used in decision making and multi criteria such as management and engineering, as well as other important domains in order to evaluate the uncertainty of real-life systems. Fuzzy reliability has proven to have effective tools and techniques based on real set theory for proposed models within various engineering fields, and current research focuses on these applications. Advancements in Fuzzy Reliability Theory introduces the concept of reliability fuzzy set theory including various methods, techniques, and algorithms. The chapters present the latest findings and research in fuzzy reliability theory applications in engineering areas. While examining the implementation of fuzzy reliability theory among various industries such as mining, construction, automobile, engineering, and more, this book is ideal for engineers, practitioners, researchers, academicians, and students interested in fuzzy reliability theory applications in engineering areas.