Search for dissertations about: "Microdata Analysis"

Showing result 6 - 10 of 55 swedish dissertations containing the words Microdata Analysis.

  2. 6. Corporate Disclosures Regulations : Social Solution or a Problem?

    Author : Asif M Huq; Kenneth Carling; Fredrik Hartwig; Arend Hintze; Moti Zwilling; Högskolan Dalarna; []
    Keywords : SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; audit choice; audit regulations; corporate governance; corporate sustainability; EU-wide accounting reforms; firm growth; greenhouse gas emissions; machine learning; microdata analysis; natural learning processing; new institutional economics; nonfinancial reporting; survey;

    Abstract : Regulations are argued to have the answer to solving various social and economic problems that society faces today (e.g., climate change, tax evasion, etc.). READ MORE

  4. 7. The Optimal trigger speed of vehicle activated signs

    Author : Diala Jomaa; Högskolan Dalarna; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; optimal trigger speed; vehicle activated sign; vehicle mean speed; standard deviation; calibration; Doppler radar; driver behaviour; data analysis; Complex Systems – Microdata Analysis; Komplexa system - mikrodataanalys;

    Abstract : The thesis aims to elaborate on the optimum trigger speed for Vehicle Activated Signs (VAS) and to study the effectiveness of VAS trigger speed on drivers’ behaviour. Vehicle activated signs (VAS) are speed warning signs that are activated by individual vehicle when the driver exceeds a speed threshold. READ MORE

  5. 8. Applications of artificial neural networks for time series data analysis in energy domain

    Author : Fan Zhang; Hasan Fleyeh; Stawomir Nowaczyk; Högskolan Dalarna; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Deregulated energy market; electricity prices; district heating; energy efficiency; neural networks; Complex Systems – Microdata Analysis; Komplexa system - mikrodataanalys;

    Abstract : With the development of artificial intelligence techniques and increased installation of smart meters in recent years, time series analysis using historical data in the energy domain becomes applicable. In this thesis, microdata analysis approaches are used, which consist of data acquisition, data processing, data analysis and data modelling, aiming to address two research problems in the energy domain. READ MORE

  6. 9. Machine learning for building energy system analysis

    Author : Fan Zhang; Johan Håkansson; Chris Bales; Stefan Byttner; Högskolan Dalarna; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; district heating; machine learning; deep learning; HVAC; neural networks;

    Abstract : Buildings account for approximately 40% of the global energy, and Heating, Ventilation, and Air Conditioning (HVAC) contributes to a large proportion of building energy consumption. Two main negative characteristics that contribute to performance degradation and energy waste in an HVAC system are inappropriate control strategies and faults. READ MORE

  7. 10. Novel Statistical Methods in Quantitative Genetics : Modeling Genetic Variance for Quantitative Trait Loci Mapping and Genomic Evaluation

    Author : Xia Shen; Örjan Carlborg; Lars Rönnegård; William Hill; Uppsala universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; statistical genetics; quantitative trait loci; genome-wide association study; genomic selection; genetic variance; hierarchical generalized linear model; linear mixed model; random effect; heteroscedastic effects model; variance-controlling genes; Complex Systems – Microdata Analysis;

    Abstract : This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. READ MORE