Kernel based neural networks with probabilistic reasoning are suitable for many practical applications. But in uence of data set sizes let the probabilistic approach fail in case of small data amounts. Possibilistic reasoning avoids this drawback because it is independent of class size. The fundamentals of possibilistic reasoning are derived from a probability/possibility consistency principle ...

Many practical control problems are so complex that traditional analysis and design methods fail to solve. Consequently, in recent years probabilistic methods that provide approximate solutions to such ’difficult’ problems have emerged. Unfortunately, the uniform random sampling process usually used in such techniques unavoidably leads to clustering of the sampled points in higher dimensions. I...

the notion of a probabilistic metric  space  corresponds to thesituations when we do not know exactly the  distance.  probabilistic metric space was  introduced by karl menger. alsina, schweizer and sklar gave a general definition of  probabilistic normed space based on the definition of menger [1]. in this note we study the pn spaces which are  topological vector spaces and the open mapping an...

Intravascular ultrasound images represent a unique tool to analyze the morphology of arteries and vessels (plaques, etc). The poor quality of these images makes traditional segmentation algorithms (such as edge detection) fail to achieve the expected results. In this paper we present a probabilistic flexible template to separate different regions in the image. In particular, we use elliptic tem...

In this paper, the connection between Menger probabilistic norms and H"{o}hle probabilistic norms is discussed. In addition, the correspondence between probabilistic norms and Wu-Fang fuzzy (semi-) norms is established. It is shown that a probabilistic norm (with triangular norm $min$) can generate a Wu-Fang fuzzy semi-norm and conversely, a Wu-Fang fuzzy norm can generate a probabilistic norm.

Strategic positioning and allocation of emergency responders and/or resources to potential incidents are very important decisions for disaster management programs. In this paper, a reliable multi-type joint-service facility location model is proposed, which takes into consideration the need cooperative service from multiple types responder stations, as well probabilistic risk station disruption...

In many industries companies are faced with disruptions from emerging technologies, from the political and legislative environment, from alternative business models or from socio-cultural shifts. To be able to anticipate, identify and manage disruptions, companies are increasingly developing and experimenting with new strategic foresight (SF) practices. The research is currently limited to expl...

Theory presented by Ashby states that the process of homeostasis is directly related to intelligence and to the ability of an individual in successfully adapting to dynamic environments or disruptions. This paper presents an artificial homeostatic system entirely under evolutionary control, composed of an extended model of the GasNet artificial neural network framework, named NSGasNet, and an a...

We present an algebraic language for the description of probabilistic and non-deterministic processes, which allows us to evaluate performance indexes as well as to check some temporal requirements: ROSA (Reasoning On Stochastic Algebras). As application, we analyse the Alternating Bit Protocol obtaining the average time to send a message, considering that channels may fail with a known probabi...