Sökning: "Metrics framework"

Visar resultat 1 - 5 av 264 uppsatser innehållade orden Metrics framework.

1. 1. Measuring the Utility of Synthetic Data : An Empirical Evaluation of Population Fidelity Measures as Indicators of Synthetic Data Utility in Classification Tasks

   Master-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

   Författare :Alexander Florean; [2024]
   Nyckelord :Synthetic Data; Machine Learning; Population Fidelity Measures; Utility Metrics; Synthetic Data Quality Evaluation; Classification Algorithms; Utility Estimation; Data Privacy; Artificial Intelligence; Experiment Framework; Model Performance Assessment; Syntetisk Data; Maskininlärning; Population Fidelity Mätvärden; Användbarhetsmätvärden; Kvalitetsutvärdering av Syntetisk Data; Klassificeringsalgoritmer; Användbarhetsutvärdering; Dataintegritet; Artificiell Intelligens; AI; Experiment Ramverk; Utvärdering av Modellprestanda;

   Sammanfattning : In the era of data-driven decision-making and innovation, synthetic data serves as a promising tool that bridges the need for vast datasets in machine learning (ML) and the imperative necessity of data privacy. By simulating real-world data while preserving privacy, synthetic data generators have become more prevalent instruments in AI and ML development. LÄS MER

3. 2. Business Model Innovation for Energy Communities : A Cross-Comparative Analysis with the Business Model Canvas in the Swedish energy market

   Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

   Författare :Sohel Abdu; [2024]
   Nyckelord :Energy Communities; Renewable Energy Systems; Business Model Canvas Innovation; Swedish Energy Policy; Prosumer engagement; Circular Energy Economy; Smart Energy Technology; Sustainable Energy Transition.; Energigemenskaper; Förnybara Energisystem; Affärsmodells Canvas Innovation; Svensk Energipolitik; Prosumer engagemang; Cirkulär Energi Ekonomi; Smart Energiteknik; Hållbar Energi Övergång;

   Sammanfattning : This thesis undertakes a thorough exploration of business models for energy communities, specifically tailored to the unique requirements of the Swedish energy sector. Its objective is to identify and evaluate global business models for energy communities, focusing on their applicability within Sweden's regulatory, market, and socio-cultural contexts. LÄS MER

4. 3. Creating a Dependency Management DevBot to Improve DeveloperWorkflows

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Michalis Kaili; Fredrik Ullman; [2023-12-04]
   Nyckelord :Development Bot; Design Science Research; DevBot Frameworks;

   Sammanfattning : Software Development Bots (DevBots) are automated tools that handle tasks in a software development setting, often used to simplify daily routines. Research within the field evaluates the use of DevBots but most focus on hard quantitative metrics (commits and pull requests) and only a few qualitative metrics such as how satisfied the developer is with the new DevBot and what frameworks could be used to build it. LÄS MER

5. 4. Data streaming provenance in advanced metering infrastructures

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Zozk Mohamed; [2023-11-24]
   Nyckelord :Advanced Metering Infrastructure; Ananke; Apache Flink; Göteborg Energi; Provenance; Stream processing; Stream Processing Engine;

   Sammanfattning : Increasing volumes of data in digital systems have made the traditional approach of gathering and storing all the data while analyzing it in bulks at periodic intervals challenging and costly. One such field is the electric grid market, which has started modernizing its aging grids into smart grids where Advanced Metering Infrastructures (AMIs) play a vital role. LÄS MER

7. 5. Despeckling Echocardiograms Using Generative Adversarial Networks

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Falk DIppel; [2023-10-23]
   Nyckelord :Generative adversarial network; deep learning; echocardiography; speckle noise; denoising; segmentation;

   Sammanfattning : Previous research had shown that generative adversarial networks (GANs) are capable of despeckling echocardiograms (echos) through image-to-image translation in real-time once trained. However, only limited information regarding the quality of denoised echos and explainability of useful GAN components is provided. LÄS MER