Sökning: "dependent data"

Visar resultat 1 - 5 av 2368 avhandlingar innehållade orden dependent data.

  1. 1. Flood Hazard Assessment in Data-Scarce Basins : Use of alternative data and modelling techniques

    Författare :Diana Fuentes-Andino; Sven Halldin; Chong-Yu Xu; Keith Beven; Giuliano Di Baldassarre; Wouter Buytaert; Uppsala universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Central America; floods; data scarcity; data quality; uncertainty analysis; regionalisation; flood frequency analysis; GLUE; hydraulic modelling; rainfall-runoff modeling; TOPMODEL; LISFLOOD-FP; GRADEX; index-flood; Muskingum-Cunge-Todini flow routing; Mellanamerika; högflöde; datakvalitet; osäkerhetsanalys; regionalisering; frekvensanalys av högflöden; GLUE; hydraulisk modellering; nederbörds-avrinningsmodeller; TOPMODEL; LISFLOOD-FP; GRADEX; indexflöde; Muskingum-Cunge-Todini flödessvarstid; Central América; inundaciones; escasez de datos; calidad de los datos; análisis de incertidumbre; regionalización; análisis de frequencia de inundación; GLUE; modelación hidraulica; modelo de lluvia-escorrentía; TOPMODEL; LISFLOOD-FP; GRADEX; índice de inundación; Muskingum-Cunge-Todini rutina de propagación de flujo;

    Sammanfattning : Flooding is of great concern world-wide, causing damage to infrastructure, property and loss of life. Low-income countries, in particular, can be negatively affected by flood events due to their inherent vulnerabilities. Moreover, data to perform studies for flood risk management in low-income regions are often scarce or lacking sufficient quality. LÄS MER

  3. 2. Nonlinear Quantile Regression for Longitudinal Data

    Författare :Andreas Karlsson; Uppsala universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; bootstrap; dependent errors; median regression; Monte Carlo simulation; panel data; repeated measures; Statistics; Statistik; Biostatistics; Biostatistik;

    Sammanfattning : The overall objective of the two papers in this thesis is to examine the properties of the weighted nonlinear quantile regression estimator for the analysis of longitudinal data. To this end, the question of which weights to be used, the bias of the estimator and the possibility to calculate confidence intervals has to be examined. LÄS MER

  4. 3. On bootstrapping survival data

    Författare :Magnus Åstrand; Göteborgs universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Bootstrap; KAplan-Meier; survival; semiiarametric; exact; dependent; KAplan-Meier;

    Sammanfattning : .... LÄS MER

  5. 4. Data-Centric AI for Software Performance Engineering - Predicting Workload Dependent and Independent Performance of Software Systems Using Machine Learning Based Approaches

    Författare :Hazem Samoaa; Chalmers tekniska högskola; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Representation Learning; Software Performance Prediction; Machine Learning; Source code Representation; Graph Neural Network; Deep Learning; Data-Centric AI;

    Sammanfattning : Context: Machine learning (ML) approaches are widely employed in various software engineering (SE) tasks. Performance, however, is one of the most critical software quality requirements. Performance prediction is estimating the execution time of a software system prior to execution. LÄS MER

  7. 5. Predictive Techniques and Methods for Decision Support in Situations with Poor Data Quality

    Författare :Rikard König; Högskolan i Skövde; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Rule Extraction; Genetic Programming; Uncertainty estimation; Machine Learning; Artificial Neural Networks; Data Mining; Information Fusion; Information technology; Informationsteknik; Teknik; Technology;

    Sammanfattning : Today, decision support systems based on predictive modeling are becoming more common, since organizations often collect more data than decision makers can handle manually. Predictive models are used to find potentially valuable patterns in the data, or to predict the outcome of some event. LÄS MER