Sökning: "auto regressive moving average"

Visar resultat 1 - 5 av 12 uppsatser innehållade orden auto regressive moving average.

  1. 1. Exchange Rate Analysis Between the U.S. Dollar and the Japanese Yen

    Kandidat-uppsats, Uppsala universitet/Statistik, AI och data science

    Författare :Yuta Sakiyama; [2023]
    Nyckelord :;

    Sammanfattning : The exchange data between the U.S. Dollar and Japanese Yen are analyzed with three models called the Auto-Regressive Integrated Moving- Average (ARIMA) model, the Generalized Auto-Regressive Conditional Heteroscedastic (GARCH) model, and the Fractional Differencing model. LÄS MER

  3. 2. Data-Driven Traffic Forecasting for Completed Vehicle Simulation: : A Case Study with Volvo Test Trucks

    Magister-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Författare :Samaneh Shahrokhi; [2023]
    Nyckelord :supervised machine learning; traffic forecasting; vehicle presence prediction; binary classification; ensemble learning; feature engineering; hyperparameter tuning; data-driven analysis;

    Sammanfattning : This thesis offers a thorough investigation into the application of machine learning algorithms for predicting the presence of vehicles in a traffic setting. The research primarily focuses on enhancing vehicle simulation by employing data-driven traffic prediction methods. The study approaches the problem as a binary classification task. LÄS MER

  4. 3. Data Trustworthiness Assessment for Traffic Condition Participatory Sensing Scenario

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Hairuo Gao; [2022]
    Nyckelord :Participatory sensing; Data trustworthiness assessment; Anomaly detection; Traffic prediction; Deep neural network; Deltagande avkänning; Bedömning av uppgifternas tillförlitlighet; Upptäckt av anomalier; Trafikprognoser; Djupt neuralt nätverk;

    Sammanfattning : Participatory Sensing (PS) is a common mode of data collection where valuable data is gathered from many contributors, each providing data from the user’s or the device’s surroundings via a mobile device, such as a smartphone. This has the advantage of cost-efficiency and wide-scale data collection. LÄS MER

  5. 4. Short-term Forecasting of EV Charging Stations Power Consumption at Distribution Scale

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Milan Clerc; [2022]
    Nyckelord :Electric Vehicles; Electrical grid; Ancillary services; Time series; Gradient Boosted Trees; Recurrent Neural Networks; ARIMA.; Elbilar; Elnät; Tidsserie; Återkommande neurala nätverk; Maskininlärning.;

    Sammanfattning : Due to the intermittent nature of renewable energy production, maintaining the stability of the power supply system is becoming a significant challenge of the energy transition. Besides, the penetration of Electric Vehicles (EVs) and the development of a large network of charging stations will inevitably increase the pressure on the electrical grid. LÄS MER

  7. 5. Machine LearningMethods for Forecasting Product Demand: A case study with telecommunications software

    D-uppsats, Handelshögskolan i Stockholm/Institutionen för nationalekonomi

    Författare :Meghan Byars; [2021]
    Nyckelord :demand forecasting; machine learning; time series forecasting; random forest; SARIMA;

    Sammanfattning : There is a lack of evidence pointing to an optimal method for demand forecasting. This paper joins the collection of studies that forecast demand using a combination of machine learning methods. LÄS MER