1,721,003 research outputs found
An Hybrid Simulation model to support decision making in a manufacturing plant
No full textThe objective of the following paper is to determine a quantitative approach is generic enough and
able to reproduce the logical steps for the construction of tools for decision support systems. The heart of the
problem is the use of simulation techniques based on the concepts of System Dynamics. A further innovation is
logged in the System Dynamics is to demonstrate how an efficient technique used in decision support systems,
not only strategic, but also tactics. The paper will consist of five sections. First we will describe the main
characteristics of the DSS and their role in decision-making. In the second section we focus will shift on the
simulation, in particular, we highlight the differences between the various techniques and its role within the
DSS . In the last few three sections it will be a case study, which will be exposed, as we were able to solve a
problem using the System Dynamics. In particular, there will be an in-depth analysis of the problem. In the
fourth will turn to an analysis of data and the description of the simulation model. Finally, in the fifth and final
section, we discuss how the simulation was carried out and the results thereof, the latter will be analyzed and be
put forward ideas for resolving the problem, the simulation will be performed again and will report the results
of various scenarios
Laguerre-type Bessel functions
No full textIn the framework of the 'monomiality principle', we introduce a class of Bessel-type functions which can be derived by applying the properties of an isomorphism, related to the so called Laguerre-type exponentials. Further extensions and possible generalizations to the multivariable case are mentioned
Story creation from heterogeneous data sources
No full textThere are numerous applications where there is a need to rapidly infer a story about a given subject from a given set of potentially heterogeneous data sources. In this paper, we formally define a story to be a set of facts about a given
subject that satisfies a “story length” constraint. An optimal story is a story that maximizes the value of an objective function measuring the goodness of a story.
We present algorithms to extract stories from text and other data sources. We also develop an algorithm to compute an optimal story, as well as three heuristic algorithms to rapidly compute a suboptimal story. We run experiments to show that constructing stories can be efficiently performed and that the stories constructed by these heuristic algorithms are high quality stories. We have built a prototype STORY system based on our model — we briefly describe the prototype as well as one application in this paper
- …
