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result(s) for
"Local measures"
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Managing multi-functional peri-urban landscapes: Impacts of horse-keeping on water quality
Eutrophication assessments in water management to quantify nutrient loads and identify mitigating measures seldom include the contribution from horse facilities. This may be due to lack of appropriate methods, limited resources, or the belief that the impact from horses is insignificant. However, the recreational horse sector is growing, predominantly in multi-functional peri-urban landscapes. We applied an ecosystem management approach to quantify nutrient loads from horse facilities in the Stockholm Region, Sweden. We found that horses increased the total loads with 30–40% P and 20–45% N, with average area-specific loads of 1.2 kg P and 7.6 kg N ha
−1
year
−1
. Identified local risk factors included manure management practices, trampling severity, soil condition and closeness to water. Comparisons of assessment methods showed that literature standard values of area-specific loads and water runoff may be sufficient at the catchment level, but in small and more complex catchments, measurements and local knowledge are needed.
Journal Article
Ensemble of surrogates with hybrid method using global and local measures for engineering design
Surrogate models are usually used as a time-saving approach to reduce the computational burden of expensive computer simulations for engineering design. However, it is difficult to choose an appropriate model for an unknown design space. To tackle this problem, an effective method is forming an ensemble model that combines several surrogate models. Many efforts were made to determine the weight factors of ensemble, which include global and local measures. This article investigates the characteristics of global and local measures, and presents a new ensemble model which combines the advantages of these two measures. In the proposed method, the design space is divided into two parts, and different strategies are introduced to evaluate the weight factors in these two parts respectively. The results from numerical and engineering design cases show that the proposed ensemble model has satisfactory robustness and accuracy (it performs best for most cases tested in this article), while spending almost the equivalent modeling time (the additional cost is not more than 6.7% for any case tested in this article) compared with the combined global and local ensemble models.
Journal Article
Polynomial Entropy of Amenable Group Actions for Noncompact Sets
In this paper, we define and study polynomial entropy on an arbitrary subset and local measure theoretic polynomial entropy for any Borel probability measure on a compact metric space, and investigate the relation between local measure-theoretic polynomial entropy of Borel probability measures and polynomial entropy on an arbitrary subset. Also, we establish a variational principle for polynomial entropy on compact subsets in the context of amenable group actions.
Journal Article
Some Remarks on Dynamical System of Solenoids
We show that a solenoid is a dynamical object and we express its complexity by a number of different entropy-like quantities in Hurley’s sense. Some relations between these entropy-like quantities are presented. We adopt the theory of Carathéodory dimension structures introduced axiomatically by Pesin to a case of a solenoid. Any of the above mentioned entropy-like quantities determines a particular Carathéodory structure such that its upper capacity coincides with the considered quantity. We mimic a definition of the local measure entropy, introduced by Brin and Katok for a single map, to a case of a solenoid. Lower estimations of these quantities by corresponding local measure entropies are described.
Journal Article
An adaptive ensemble of surrogate models based on hybrid measure for reliability analysis
When dealing with complex reliability problems, the classical ensemble of surrogate models (CESM) has better ability of prediction and generalization than the individual surrogate model. However, since the CESM only considers the global errors of the sample set, the prediction results of the sample points far away from the region where most of the samples gather might not be so accurate, and the fitting accuracy of the limit state function will also be affected when the sample points are sparse. In view of the above situation, this paper proposes an adaptive ensemble of surrogate models based on hybrid measure (AESMHM), which comprehensively considers the global errors and local errors. The global weight matrix is modified by the local weight matrix of representative sample points to obtain the hybrid weight of each surrogate model. Through the discussion of four examples, it can be proved that AESMHM can not only improve the prediction accuracy of the whole sample points, but also have higher computational efficiency. Finally, the reliability problem of a radome structure in composite material is solved efficiently by the proposed method.
Journal Article
Localized Spatiotemporal Effects in the Determinants of Property Prices: A Case Study of Seoul
This research investigates both spatial and temporal elements of the apartment pricing process in Seoul, South Korea by modeling the determinants of apartment prices over a ten-year period from 2006 to 2015 with a hedonic price model containing a spatio-temporal lag model calibrated by geographically weighted regression (GWR). The results yield information on both spatial and temporal variations in the processes affecting apartment prices and demonstrate the use of GWR for generating local spatial dependency measures which are conditioned on various covariates rather than being simple descriptions of pattern. The study utilizes a combined approach to account for both spatial dependency in housing prices and spatial heterogeneity in the processes generating those prices. The results suggest that there are spatial variations in the determinants of apartment prices and that these spatial variations are fairly consistent over time. The effect of the spatial lag on house prices exhibits strong spatial variation which again is reasonably consistent over time.
Journal Article
Connectivity of random graphs after centrality-based vertex removal
Centrality measures aim to indicate who is important in a network. Various notions of ‘being important’ give rise to different centrality measures. In this paper, we study how important the central vertices are for the connectivity structure of the network, by investigating how the removal of the most central vertices affects the number of connected components and the size of the giant component. We use local convergence techniques to identify the limiting number of connected components for locally converging graphs and centrality measures that depend on the vertex’s neighbourhood. For the size of the giant, we prove a general upper bound. For the matching lower bound, we specialise to the case of degree centrality on one of the most popular models in network science, the configuration model, for which we show that removal of the highest-degree vertices destroys the giant most.
Journal Article
Dynamical integrity assessment of stable equilibria: a new rapid iterative procedure
A new algorithm for the estimation of the robustness of a dynamical system’s equilibrium is presented. Unlike standard approaches, the algorithm does not aim to identify the entire basin of attraction of the solution. Instead, it iteratively estimates the so-called local integrity measure, that is, the radius of the largest hypersphere entirely included in the basin of attraction of a solution and centred in the solution. The procedure completely overlooks intermingled and fractal regions of the basin of attraction, enabling it to provide a significant engineering quantity in a very short time. The algorithm is tested on four different mechanical systems of increasing dimension, from 2 to 8. For each system, the variation of the integrity measure with respect to a system parameter is evaluated, proving the engineering relevance of the results provided. Despite some limitations, the algorithm proved to be a viable alternative to more complex and computationally demanding methods, making it a potentially appealing tool for industrial applications.
Journal Article