Perhaps the most promising reductionist view about chance is Lewis' best system analysis of probabilistic laws (Lewis, 1994; Loewer, 2004).
We concentrate on Takagi Sugeno (TS) probabilistic fuzzy systems that combine interpretability of fuzzy systems with the statistical properties of probabilistic systems.
Were the neural networks to be useful to such a mapping, they could in principle be employed for several purposes, such as soil identification using instrumental data, design of early warning systems and estimation of probabilistic spectra via Monte Carlo simulation, in which the ANN act as an efficient solver surrogate.
When we build network models for a series of biological systems (e.g., cell lines or patient derived samples) with similar but distinct genomic properties, the BP-generated probability distributions in one cellular system can be extrapolated to another system as a set of probabilistic biases (i.e., priors).
Total cost distributions of the system, probabilistic capacities of the technologies in the system and the basic life-support element amounts that are needed to support crew life and activities for the duration of a given mission are determined using the proposed framework.
In order to a reliable operation of power system, a probabilistic approach of network congestion for reliability analysis is used in this paper, which embeds the deterministic framework within a probabilistic approach.
This effectiveness can be attributed largely to two factors: the use of contextual features by the machine learning system and the use of probabilistic evidence.
We define a logic EpCTL for reasoning about the evolution of probabilistic systems.
Quantum mechanics tells us, at least according to some interpretations, that the behavior of probabilistic systems is, in some respects, easy to predict.
Conditional independence is a crucial notion in the development of probabilistic systems which are successfully employed in areas such as computer vision, computational biology, and natural language processing.
