Modern Probability Theory and its Applications.

FUZZY SOFT SET THEORY AND ITS APPLICATIONS

In this work, we define a fuzzy soft set theory and its related properties. We then define fuzzy soft aggregation operator that allows constructing more efficient decision making method. Finally, we give an example which shows that the method can be successfully applied to many problems that contain uncertainties.

Algorithmic Probability—Theory and Applications

We first define Algorithmic Probability, an extremely powerful method of inductive inference. We discuss its completeness, incomputability, diversity and subjectivity and show that its incomputability in no way inhibits its use for practical prediction. Applications to Bernoulli sequence prediction and grammar discovery are described. We conclude with a note on its employment in a very strong A...

Probability theory and its models

This paper argues for the status of formal probability theory as a mathematical, rather than a scientific, theory. David Freedman and Philip Stark’s concept of model based probabilities is examined and is used as a bridge between the formal theory and applications.

fuzzy soft set theory and its applications

in this work, we define a fuzzy soft set theory and its related properties. we then define fuzzy soft aggregation operator that allows constructing more efficient decision making method. finally, we give an example which shows that the method can be successfully applied to many problems that contain uncertainties.

Applications of Probability: Benford’s Law and Hypothesis Testing from an Invitation to Modern Number Theory