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Hierarchical Process (hierarchical + process)
Selected AbstractsAn AHP/DEA methodology for ranking decision making unitsINTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, Issue 2 2000Z. Sinuany-Stern Abstract This paper presents a two-stage model for fully ranking organizational units where each unit has multiple inputs and outputs. In the first stage, the Data Envelopment Analysis (DEA) is run for each pair of units separately. In the second stage, the pairwise evaluation matrix generated in the first stage is utilized to rank scale the units via the Analytical Hierarchical Process (AHP). The consistency of this AHP/DEA evaluation can be tested statistically. Its goodness of fit with the DEA classification (to efficient/inefficient) can also be tested using non-parametric tests. Both DEA and AHP are commonly used in practice. Both have limitations. The hybrid model AHP/DEA takes the best of both models, by avoiding the pitfalls of each. The nonaxiomatic utility theory limitations of AHP are irrelevant here: since we are working with given inputs and outputs of units, no subjective assessment of a decision maker evaluation is involved. AHP/DEA ranking does not replace the DEA classification model, rather it furthers the analysis by providing full ranking in the DEA context for all units, efficient and inefficient. [source] Predictive models of habitat preferences for the Eurasian eagle owl Bubo bubo: a multiscale approachECOGRAPHY, Issue 1 2003Jose Antonio Martínez Habitat preference of eagle owls Bubo bubo were examined through comparing habitat composition around 51 occupied cliffs and 36 non-occupied cliffs in Alicante (E Spain). We employed Generalized Linear Models to examine patterns of habitat preference at three different spatial scales: nest site (7 km2), home range (25 km2), and landscape (100 km2). At the nest site scale, occupied cliffs were more rugged, had a greater proportion of forest surface in the surroundings, and were further from the nearest paved road than unoccupied cliffs. Additionally, probability of having an occupied cliff increased when there was another occupied territory in the surroundings. At both the home range scale and the landscape scale, high probabilities of presence of eagle owls were related to high percentages of Mediterranean scrubland around the cliffs, which are the preferred habitat of European rabbits Oryctolagus cuniculus, the main prey of the owls. We suggest a hierarchical process of habitat selection in the eagle owl concerning suitable trophic resources at the broadest scales and adequate sites for breeding and roosting at the smallest scale. However, it should be noted that some structural features such as the proximity of roads were not necessarily avoided by the owls, but their presence were possibly constrained by systematic killing of individuals. Our paper provides new evidence for the requirement of multi-scale approaches to gain insight into both the different limiting factors for the persistence of populations and the role of individual perception of the environment in the evolution of habitat selection. [source] The quest for a null model for macroecological patterns: geometry of species distributions at multiple spatial scalesECOLOGY LETTERS, Issue 8 2008David Storch Abstract There have been several attempts to build a unified framework for macroecological patterns. However, these have mostly been based either on questionable assumptions or have had to be parameterized to obtain realistic predictions. Here, we propose a new model explicitly considering patterns of aggregated species distributions on multiple spatial scales, the property which lies behind all spatial macroecological patterns, using the idea we term ,generalized fractals'. Species' spatial distributions were modelled by a random hierarchical process in which the original ,habitat' patches were randomly replaced by sets of smaller patches nested within them, and the statistical properties of modelled species assemblages were compared with macroecological patterns in observed bird data. Without parameterization based on observed patterns, this simple model predicts realistic patterns of species abundance, distribution and diversity, including fractal-like spatial distributions, the frequency distribution of species occupancies/abundances and the species,area relationship. Although observed macroecological patterns may differ in some quantitative properties, our concept of random hierarchical aggregation can be considered as an appropriate null model of fundamental macroecological patterns which can potentially be modified to accommodate ecologically important variables. [source] Performance optimization of object comparisonINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 10 2009Axel Hallez Comparing objects can be considered as a hierarchical process. Separate aspects of objects are compared to each other, and the results of these comparisons are combined into a single result in one or more steps by aggregation operators. The set of operators used to compare the objects and the way these operators are related with each other is called the comparison scheme. If a threshold is applied to the final result of the object comparison, the mathematical properties of the operators in the comparison scheme can be used to derive thresholds on the intermediate results. These derived threshold can be used to break of a comparison early, thus offering a reduction of the comparison cost. Using this information, we show that the order in which the operators are evaluated has an influence on the average cost of comparing two objects. Next, we proceed with a study of the properties that allow us to find an optimal order, such that this average cost is minimized. Finally, we provide an algorithm that calculates an optimal order efficiently. Although specifically developed for object comparison, the algorithm can be applied to all kinds of selection processes that involve the combination of several test results. © 2009 Wiley Periodicals, Inc. [source] | ||||||||||