An Introduction To The Neutrosophic Probability And Nuetrosophic Statistics
Download An Introduction To The Neutrosophic Probability And Nuetrosophic Statistics full books in PDF, epub, and Kindle. Read online free An Introduction To The Neutrosophic Probability And Nuetrosophic Statistics ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author | : Florentin Smarandache |
Publisher | : Infinite Study |
Total Pages | : 125 |
Release | : 2014 |
Genre | : Mathematics |
ISBN | : 1599732742 |
Neutrosophic Statistics means statistical analysis of population or sample that has indeterminate (imprecise, ambiguous, vague, incomplete, unknown) data. For example, the population or sample size might not be exactly determinate because of some individuals that partially belong to the population or sample, and partially they do not belong, or individuals whose appurtenance is completely unknown. Also, there are population or sample individuals whose data could be indeterminate. In this book, we develop the 1995 notion of neutrosophic statistics. We present various practical examples. It is possible to define the neutrosophic statistics in many ways, because there are various types of indeterminacies, depending on the problem to solve.
Author | : FLORENTIN SMARANDACHE |
Publisher | : Infinite Study |
Total Pages | : 15 |
Release | : |
Genre | : |
ISBN | : |
This project is a part of a National Science Foundation interdisciplinary project proposal. Starting from a new viewpoint in philosophy, the neutrosophy, one extends the classical "probability theory", "fuzzy set" and "fuzzy logic" to , and respectively.
Author | : Florentin Smarandache |
Publisher | : |
Total Pages | : |
Release | : 1999-12 |
Genre | : |
ISBN | : 9781879585737 |
Author | : Florentin Smarandache |
Publisher | : Infinite Study |
Total Pages | : 18 |
Release | : 2022-06-01 |
Genre | : Mathematics |
ISBN | : |
In this paper, we prove that Neutrosophic Statistics is more general than Interval Statistics, since it may deal with all types of indeterminacies (with respect to the data, inferential procedures, probability distributions, graphical representations, etc.), it allows the reduction of indeterminacy, and it uses the neutrosophic probability that is more general than imprecise and classical probabilities and has more detailed corresponding probability density functions. While Interval Statistics only deals with indeterminacy that can be represented by intervals. And we respond to the arguments by Woodall et al. [1]. We show that not all indeterminacies (uncertainties) may be represented by intervals. Also, in some cases, we should better use hesitant sets (that have less indeterminacy) instead of intervals. We redirect the authors to the Plithogenic Probability and Plithogenic Statistics which are the most general forms of MultiVariate Probability and Multivariate Statistics respectively (including, of course, the Imprecise Probability and Interval Statistics as subclasses).
Author | : Florentin Smarandache |
Publisher | : Infinite Study |
Total Pages | : 11 |
Release | : |
Genre | : |
ISBN | : |
In this paper one generalizes the classical probability and imprecise probability to the notion of “neutrosophic probability” in order to be able to model Heisenberg’s Uncertainty Principle of a particle’s behavior, Schrödinger’s Cat Theory, and the state of bosons which do not obey Pauli’s Exclusion Principle (in quantum physics).
Author | : Florentin Smarandache |
Publisher | : Infinite Study |
Total Pages | : 157 |
Release | : 2005 |
Genre | : Mathematics |
ISBN | : 1599730804 |
N-Norm and N-conorm are extended in Neutrosophic Logic/Set.
Author | : Florentin Smarandache |
Publisher | : Infinite Study |
Total Pages | : 142 |
Release | : |
Genre | : |
ISBN | : 159973253X |
In this book, we introduce for the first time the notions of neutrosophic measure and neutrosophic integral, and we develop the 1995 notion of neutrosophic probability. We present many practical examples. It is possible to define the neutrosophic measure and consequently the neutrosophic integral and neutrosophic probability in many ways, because there are various types of indeterminacies, depending on the problem we need to solve. Neutrosophics study the indeterminacy. Indeterminacy is different from randomness. It can be caused by physical space materials and type of construction, by items involved in the space, etc.
Author | : Florentin Smarandache |
Publisher | : |
Total Pages | : 110 |
Release | : 1998 |
Genre | : Mathematics |
ISBN | : |
Author | : Haibin Wang |
Publisher | : Infinite Study |
Total Pages | : 99 |
Release | : 2005 |
Genre | : Mathematics |
ISBN | : 1931233942 |
This book presents the advancements and applications of neutrosophics, which are generalizations of fuzzy logic, fuzzy set, and imprecise probability. The neutrosophic logic, neutrosophic set, neutrosophic probability, and neutrosophic statistics are increasingly used in engineering applications (especially for software and information fusion), medicine, military, cybernetics, physics.In the last chapter a soft semantic Web Services agent framework is proposed to facilitate the registration and discovery of high quality semantic Web Services agent. The intelligent inference engine module of soft semantic Web Services agent is implemented using interval neutrosophic logic.
Author | : Florentin Smarandache editor |
Publisher | : Infinite Study |
Total Pages | : 148 |
Release | : 2003-01-01 |
Genre | : Mathematics |
ISBN | : 1931233675 |
Collected papers on neutrosophics [such as: ?neutrosophy? - a new branch of philosophy, ?neutrosophic logic? ? a generalization of the fuzzy logic, ?neutrosophic set? ? a generalization of the fuzzy set, and ?neutrosophic probability? ? a generalization of classical probability and imprecise probability] by Florentin Smarandache, Jean Dezert, Andrzej Buller, Mohammad Khoshnevisan, Sarjinder Singh, Sukanto Bhattacharya, Feng Liu, Gh. C. Dinulescu-Campina, Chris Lucas, and Carlos Gershenson.Neutrosophic Logic involved the foundation of the Dezert-Smarandache Theory of Plausible and Paradoxical Reasoning, which has taken into consideration the combination of uncertain and contradictory information, used now in artificial intelligence.