Search results for "A* algorithm"
showing 10 items of 2538 documents
Feature Ranking of Large, Robust, and Weighted Clustering Result
2017
A clustering result needs to be interpreted and evaluated for knowledge discovery. When clustered data represents a sample from a population with known sample-to-population alignment weights, both the clustering and the evaluation techniques need to take this into account. The purpose of this article is to advance the automatic knowledge discovery from a robust clustering result on the population level. For this purpose, we derive a novel ranking method by generalizing the computation of the Kruskal-Wallis H test statistic from sample to population level with two different approaches. Application of these enlargements to both the input variables used in clustering and to metadata provides a…
A simple algorithm for retrieval of the optical thickness at L-band from SMOS data
2012
Vegetation indices are indicators for analyzing the properties of vegetation. The Normalized Difference Vegetation Index (NDVI) from optical remote sensing data is one of the most commonly used vegetation indices, which can exhibit the ecological characteristics of leafy materials, but lacks the ability to directly provide information on the woody materials. In this paper, we developed Microwave Vegetation Indices (MVIs) from the L-band Soil Moisture and Ocean Salinity (SMOS) data, which is an effective means to detect the information of branches and trunks. The theory of MVIs is derived from the tau-omega model. To minimize the influence from the uncertain soil surface radiation, a paramet…
Generalizing LARS algorithm using differential geometry
2009
We propose a path following algorithm for generalized linear models that can be considered a differential geometric generalization of the LARS algorithm. In our approach we use differential geometry to generalize the equiangular condition on which is based the LARS algorithm and then we use a predictor-corrector method to compute the solution path of the coefficients.
Panel Summary: Behavioural Models
1997
The aim of this paper is to report the panel discussion on behavioural models of human or machine agents interacting with the environment. In particular the following hot points will been analysed: a framework for describing behaviour; learning and evolution; closure and teleonomy when it comes to behaviour; the perception-learning-planning loop; the information integration at the (pre)attentive level; knowing by acting and knowing by computing.
Calibration and Validation of Thermal Infrared Remote Sensing Sensors and Land/Sea Surface Temperature algorithms over the Iberian Peninsula
2017
La Temperatura de la Superficie Terrestre (TST) y la Temperatura de la Superficie del Mar (TSM) son parámetros clave en los procesos físicos de intercambio de energía entre la superficie y la atmósfera. La TST/TSM están directamente relacionadas con el espectro Infrarrojo Térmico (TIR) que constituye la principal fuente de emisión de radiación de la superficie terrestre. El control de los datos térmicos se puede realizar con la Calibración Vicarea (VC) para, de esta forma, garantizar la calidad de los datos una vez el sensor a bordo de satélite está en órbita. Normalmente, la validación directa de los algoritmos de TST y la VC del espectro térmico se realiza con datos in-situ en tierra, mie…
Unobserved Heterogeneity in Overeducation Models: Is Personality More Important than Ability?
2013
This paper compares the performance of selected personality aspects and ability on explaining the overeducation status of the individual. Ability is defined as the difference between the actual and the predicted income. Personality proves to be an important factor affecting the risk of overeducation. For females, personality allows to better explain mismatch than ability. For males, ability frequently, but not always, performs better than personality. Controlling for personality allows for better classification of the non-overeducated, while controlling for ability improves the classification of the overeducated. The study is done on the pooled sample of 23 European countries, as well as fo…
Perdersi. Note sul Labirinto
2022
The paper is inspired by a conversation of its author with Sandro Man- cini. Through a series of self-biographical notes, it tries to examine the topological gure of the labyrinth in some of its main mythical- symbolic, mathematical and conceptual articulations. Starting from a famous essay by Italo Calvino, i.e. La s da al labirinto, it seeks in par- ticular to discuss the works of Pierre Rosenstiehl, mathematician and philosopher to whom we owe some of the most re ned analyses on the subject of labyrinth. In the conclusions, after some other short intro- spective remarks, one aims at raising the necessity of more systematic and deepened investigations about this subject.
Improving transferability strategies for debris flow susceptibility assessment: Application to the Saponara and Itala catchments (Messina, Italy)
2017
Abstract Debris flows can be described as rapid gravity-induced mass movements controlled by topography that are usually triggered as a consequence of storm rainfalls. One of the problems when dealing with debris flow recognition is that the eroded surface is usually very shallow and it can be masked by vegetation or fast weathering as early as one-two years after a landslide has occurred. For this reason, even areas that are highly susceptible to debris flow might suffer of a lack of reliable landslide inventories. However, these inventories are necessary for susceptibility assessment. Model transferability, which is based on calibrating a susceptibility model in a training area in order t…
Size-intensive decomposition of orbital energy denominators
2000
We introduce an alternative to Almlöf and Häser’s Laplace transform decomposition of orbital energy denominators used in obtaining reduced scaling algorithms in perturbation theory based methods. The new decomposition is based on the Cholesky decomposition of positive semidefinite matrices. We show that orbital denominators have a particular short and size-intensive Cholesky decomposition. The main advantage in using the Cholesky decomposition, besides the shorter expansion, is the systematic improvement of the results without the penalties encountered in the Laplace transform decomposition when changing the number of integration points in order to control the convergence. Applications will…
An affine scaling method using a class of differential barrier functions: primal approach
2020
International audience; In this paper we propose a family of affine scaling interior point algorithms, called galpv4, using a primal approach, based on a large class of differential barrier functions. We show that these algorithms are in fact an extension and generalization of the classical affine scaling algorithm based on the well-known log barrier function. After carrying out a complete convergence analysis, we select some of these algorithms for comparison with the classical affine scaling algorithm, performed with the help of the familiar Netlib test set.