Results 21 to 30 of about 1,817,965 (264)

Applications of Robust Methods in Spatial Analysis

Journal of Probability and Statistics, 2023
Spatial data analysis provides valuable information to the government as well as companies. The rapid improvement of modern technology with a geographic information system (GIS) can lead to the collection and storage of more spatial data.
Selvakkadunko Selvaratnam
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CLUSTERING INCOMPLETE SPECTRAL DATA WITH ROBUST METHODS [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017
Missing value imputation is a common approach for preprocessing incomplete data sets. In case of data clustering, imputation methods may cause unexpected bias because they may change the underlying structure of the data.
S. Äyrämö, I. Pölönen, M. A. Eskelinen   +2 more
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Robust analysis of the central tendency, simple and multiple regression and ANOVA: a step by step tutorial.

International Journal of Psychological Research, 2010
After much exertion and care to run an experiment in social science, the analysis of data should not be ruined by an improper analysis. Often, classical methods, like the mean, the usual simple and multiple linear regressions, and the ANOVA require ...
Delphine S. Courvoisier, Olivier Renaud
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genieclust: Fast and robust hierarchical clustering

SoftwareX, 2021
genieclust is an open source Python and R package that implements the hierarchical clustering algorithm called Genie. This method frequently outperforms other state-of-the-art approaches in terms of clustering quality and speed, supports various ...
Marek Gagolewski
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Methods for Evolving Robust Programs [PDF]

, 2003
Many evolutionary computation search spaces require fitness assessment through the sampling of and generalization over a large set of possible cases as input. Such spaces seem particularly apropos to Genetic Programming, which notionally searches for computer algorithms and functions.
Liviu Panait, Sean Luke
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Robust Methods for Assessing the Characteristics of Locomotor Activity Based on Markerless Video Capture Data

Известия высших учебных заведений России: Радиоэлектроника
Introduction. Analysis of locomotor activity is essential in a number of biomedical and pharmacological research designs, as well as environmental monitoring.
M. I. Bogachev, K. R. Grigarevichius, N. S. Pyko, S. A. Pyko, M. Tsygankova, E. A. Plotnikova, T. V. Ageeva, Ya. O. Mukhamedshina   +7 more
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Robust optimization in production engineering – methods and application [PDF]

E3S Web of Conferences, 2019
Methods that use robust optimization are aimed at finding robustness to decision uncertainty. Uncertainty may affect the input parameters (problem) and the final solution. Robust optimization is applicable in many areas, such as: operational research, IT,
Knapczyk Adrian, Francik Sławomir, Jewiarz Marcin, Mudryk Krzysztof, Wróbel Marek   +4 more
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Uncertainty-Aware Deep Learning Methods for Robust Diabetic Retinopathy Classification

IEEE Access, 2022
Automatic classification of diabetic retinopathy from retinal images has been increasingly studied using deep neural networks with impressive results.
Joel Jaskari, Jaakko Sahlsten, Theodoros Damoulas, Jeremias Knoblauch, Simo Sarkka, Leo Karkkainen, Kustaa Hietala, Kimmo K. Kaski   +7 more
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Robust Statistical Methods with R

Journal of Statistical Software, 2006
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Jan de Leeuw
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Modified H∞ loop-shaping procedure for the two degrees-of-freedom control configuration of an UAV (ARCHER V 1.7) [PDF]

INCAS Bulletin
The robust stabilization problem with respect to both dynamic and parametric uncertainty for linear deterministic systems is analyzed in the present article.
Adrian BURGHIU, Adrian-Mihail STOICA
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