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Contributions of Brunswik's Theory of Probabilistic Functionalism.
Theoretical studies are made to analyze the global convergence of cPSO and cQPSO-lbest based on the theory of probabilistic metric space.
Roland Scholz and his team have done a fine job of drawing attention to what they see as the important insights contained in Brunswik's Theory of Probabilistic Functionalism (TPF).
The methods developed so far integrate on the one side the theory of probabilistic systems (master equation) and of nonlinear dynamics, and on the other side overarching concepts (such as dynamic utilities) from the social sciences.
Since then, the theory of probabilistic metric spaces has been developed in many directions [1].
Random metric theory originated from the theory of probabilistic metric spaces [1].
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Causal decision theory, in particular, the version using dependency hypotheses, grounds theories of probabilistic causation.
The new theory of fundamental probabilistic structures was developed later on by many authors.
In the sequel, we will adopt usual terminology, notation, and conventions of the theory of Menger probabilistic metric spaces, as in [7, 8, 10].
The theory of a probabilistic metric space is an active field and has applications in many other branches of mathematics such as cluster analysis, mathematical statistics and chaos theory [3, 4].
Firstly, by virtue of the theory of non-probabilistic interval process, an interval process model of fatigue crack propagation is investigated, in which we describe uncertain crack length a(N) at any load cycle N as interval variable and define the corresponding auto-covariance function and the correlation coefficient function to further characterize the correlation of a(N) at different cycles.
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