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Visar resultat 1 - 5 av 455 uppsatser som matchar ovanstående sökkriterier.

  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. The Role of Uni- and Multivariate Bias Adjustment Methods for Future Hydrological Projections and Subsequent Decision-Making

    Master-uppsats, Uppsala universitet/Luft-, vatten- och landskapslära

    Författare :Anna Merle Liebenehm-Axmann; [2024]
    Nyckelord :Bias adjustment methods; future hydrological climate projections; statistical analysis; future streamflow analysis; biasjusteringsmetoder; framtida hydrologiska projektioner; statistisk analys; framtida vattenförings analys;

    Sammanfattning : Climate models are essential for generating future climate projections. However, due to simplifications, the models can produce systematic differences between output and reality, which is referred to as model bias. Bias adjustment methods aim to reduce this error, which is important for making future projections more reliable. LÄS MER

  4. 3. Machine Learning model applied to Reactor Dynamics

    Master-uppsats, KTH/Fysik

    Författare :Dionysios Dimitrios Nikitopoulos; [2023]
    Nyckelord :Master Thesis; Machine Learning; stability; Energy distribution profiles; Prediction; frequency; decay ratio; Data processing; POLCA-T; Pytorch; testing data; RMSE. ii;

    Sammanfattning : This project’s idea revolved around utilizing the most recent techniques in MachineLearning, Neural Networks, and Data processing to construct a model to be used asa tool to determine stability during core design work. This goal will be achieved bycollecting distribution profiles describing the core state from different steady statesin five burn-up cycles in a reactor to serve as the dataset for training the model. LÄS MER

  5. 4. Stock market analysis with a Markovian approach: Properties and prediction of OMXS30

    Kandidat-uppsats, KTH/Matematisk statistik

    Författare :Max Aronsson; Anna Folkesson; [2023]
    Nyckelord :Markov chain; OMXS30; Markov chain properties; voting ensemble model; markovkedja; OMXS30; egenskaper hos markovkedjor; ensemble-modell;

    Sammanfattning : This paper investigates how Markov chain modelling can be applied to the Swedish stock index OMXS30. The investigation is two-fold. Firstly, a Markov chain is based on index data from recent years, where properties such as transition matrix, stationary distribution and hitting time are studied. LÄS MER

  7. 5. Wastewater Characterisation for Design and Modelling of Primary Settlers at Municipal Wastewater Treatment Plants

    Master-uppsats, Lunds universitet/Industriell elektroteknik och automation

    Författare :Louise Westin; [2023]
    Nyckelord :Primary Settling Tank; Wastewater Treatment; Settleometer; Particle Settling Velocity Distribution; Modelling.; Technology and Engineering;

    Sammanfattning : The primary settling tank (PST) is often one of the first treatment steps at a wastewater treatment plant (WWTP) and is the first process in the plant to remove significant amounts of suspended solids. Its role in wastewater treatment however, has oftentimes been neglected and little effort has been made to optimize and model the process. LÄS MER