0000000001133405
AUTHOR
Jessica Havelock
Novel Distance Estimation Methods Using 'Stochastic Learning on the Line' Strategies
In this paper, we consider the problem of Distance Estimation (DE) when the inputs are the $x$ and $y$ coordinates (or equivalently, the latitudinal and longitudinal positions) of the points under consideration. The aim of the problem is to yield an accurate value for the real (road) distance between the points specified by the latter coordinates. 1 This problem has, typically, been tackled by utilizing parametric functions called the “Distance Estimation Functions” (DEFs). The parameters are learned from the training data (i.e., the true road distances) between a subset of the points under consideration. We propose to use Learning Automata (LA)-based strategies to solve the problem. In par…
On Using “Stochastic Learning on the Line” to Design Novel Distance Estimation Methods
In this paper, we consider the problem of Distance Estimation (DE) when the inputs are the x and y coordinates of the points under consideration. The aim of the problem is to yield an accurate value for the real (road) distance between the points specified by the latter coordinates. This problem has, typically, been tackled by utilizing parametric functions called Distance Estimation Functions (DEFs). The parameters are learned from the training data (i.e., the true road distances) between a subset of the points under consideration. We propose to use Learning Automata (LA)-based strategies to solve the problem. In particular, we resort to the Adaptive Tertiary Search (ATS) strategy, propose…
On Using “Stochastic Learning on the Line” to Design Novel Distance Estimation Methods for Three-Dimensional Environments
We consider the unsolved problem of Distance Estimation (DE) when the inputs are the x and y coordinates (i.e., the latitudinal and longitudinal positions) of the points under consideration, and the elevation/altitudes of the points specified, for example, in terms of their z coordinates (3DDE). The aim of the problem is to yield an accurate value for the real (road) distance between the points specified by all the three coordinates of the cities in question (This is a typical problem encountered in a GISs and GPSs.). In our setting, the distance between any pair of cities is assumed to be computed by merely having access to the coordinates and known inter-city distances of a small subset o…
On using "Stochastic learning on the line" to design novel distance estimation methods
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