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Data probes, vertical trajectories and classification: a tentative study

100%
Pearson D. W.
International Journal of Applied Mathematics and Computer Science
|
2007
|
tom 17
|
nr 1
107-112
EN
In this paper we introduce a method of classification based on data probes. Data points are considered as point masses in space and a probe is simply a particle that is launched into the space. As the probe passes by data clusters, its trajectory will be influenced by the point masses. We use this information to help us to find vertical trajectories. These are trajectories in the input space that are mapped onto the same value in the output space and correspond to the data classes.
2
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Confidence and self-confidence: Perceived and real

100%
Pearson D. W.
International Journal of Applied Mathematics and Computer Science
|
2002
|
tom 12
|
nr 2
277-283
EN
The problem of modelling the dynamics of confidence levels between two individuals is investigated. A model, based on a master equation approach, is developed and presented. An important feature of the model is that self-confidence is modelled along with its interaction with confidence towards others. Simulation results are presented.
3
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Dynamics of social networks: A deterministic approach

63%
Pearson D. W., McCartney M.
International Journal of Applied Mathematics and Computer Science
|
2002
|
tom 12
|
nr 4
545-551
EN
Our aim is to model the dynamics of social networks, which comprises the problem of how people get to know each other, like each other, detest each other, etc. Most existing models are stochastic in nature and, obviously, based on random events. Our approach is deterministic and based on ordinary differential equations. This should not be seen as a challenge to stochastic models, but rather as a complement.
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