Search results for " Landscape analysis"
showing 3 items of 3 documents
Plant hunting: exploring the behaviour of amateur botanists in the field
2021
We asked what are the behavioural and logistic preferences of professional and amateur botanists when exploring flora in the field. We extracted temporal and spatial data on vas- cular plant species occurrences from three datasets of Sicilian flora: a subset of iNaturalist, a dataset collected by a Facebook group focused on the flora of Sicily and a subset of the professional database European Vegetation Archive. We used the time span of individual contributor’s activity as a proxy of their commitment to collecting information about the flora of Sicily. Climate and landscape data were used to better characterize the spatial and temporal activity of data contributors. Finally, we assessed wh…
Coarse-Grained Barrier Trees of Fitness Landscapes
2016
Recent literature suggests that local optima in fitness landscapes are clustered, which offers an explanation of why perturbation-based metaheuristics often fail to find the global optimum: they become trapped in a sub-optimal cluster. We introduce a method to extract and visualize the global organization of these clusters in form of a barrier tree. Barrier trees have been used to visualize the barriers between local optima basins in fitness landscapes. Our method computes a more coarsely grained tree to reveal the barriers between clusters of local optima. The core element is a new variant of the flooding algorithm, applicable to local optima networks, a compressed representation of fitnes…
Automatic surrogate modelling technique selection based on features of optimization problems
2019
A typical scenario when solving industrial single or multiobjective optimization problems is that no explicit formulation of the problem is available. Instead, a dataset containing vectors of decision variables together with their objective function value(s) is given and a surrogate model (or metamodel) is build from the data and used for optimization and decision-making. This data-driven optimization process strongly depends on the ability of the surrogate model to predict the objective value of decision variables not present in the original dataset. Therefore, the choice of surrogate modelling technique is crucial. While many surrogate modelling techniques have been discussed in the liter…