Essays about: "Time Series prognoser"

Showing result 11 - 15 of 47 essays containing the words Time Series prognoser.

  1. 11. On Modelling Ancillary Services Markets: A Time Series Approach

    University essay from KTH/Matematik (Avd.)

    Author : Erik Murray; [2022]
    Keywords : ARIMA; SARIMA; GARCH; load balancing; ancillary services; electrical grids; FCR-D; ARIMA; SARIMA; GARCH; lastbalans; stödtjänster; kraftnät; FCR-D 2;

    Abstract : So-called ancillary services (AS) have always been critically important for the functioning of an electrical grid, and are becoming even more so with the advent of renewable energy sources. Ancillary services are traded on open markets, and trading on these markets is arguably even more difficult to model than on traditional markets. READ MORE

  3. 12. Machine learning embedded automation in financial forecasting : A quantitative case study at Ericsson

    University essay from KTH/Skolan för industriell teknik och management (ITM)

    Author : Isak Hassbring; [2022]
    Keywords : ;

    Abstract : In today’s increasingly data-driven world, time series forecasting is becoming a prevalent practice. Business executives can make better decisions aided by insights from financial forecasts. READ MORE

  4. 13. An evaluation of deep learning models for urban floods forecasting

    University essay from KTH/Geoinformatik

    Author : Yang Mu; [2022]
    Keywords : Urban flooding forecasting; Convolutional neural networks; Deep learning; Physically-based simulation; Recurrent neural network; Stadsöversvämningsprognoser; konvolutionella neurala nätverk; djupinlärning; fysiskt baserad simulering; återkommande neurala nätverk;

    Abstract : Flood forecasting maps are essential for rapid disaster response and risk management, yet the computational complexity of physically-based simulations hinders their application for efficient high-resolution spatial flood forecasting. To address the problems of high computational cost and long prediction time, this thesis proposes to develop deep learning neural networks based on a flood simulation dataset, and explore their potential use for flood prediction without learning hydrological modelling knowledge from scratch. READ MORE

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

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

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

    Abstract : 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. READ MORE

  6. 15. High Frequency Demand Forecasting : The Case of a Swedish Pharmacy Retailer

    University essay from KTH/Skolan för industriell teknik och management (ITM)

    Author : Aban Saleem; [2022]
    Keywords : Retail; Forecast; Pharmacy; SARIMA; Holt-Winter’s method; Facebook Prophet; high-frequency; Retail; Prognos; Pharmacy; SARIMA; Holt-Winter’s metod; Face- book Prophet; hög frekvens;

    Abstract : Predicting future sales can bring many advantages to retailers with regards to organizational performance. Using big data to make accurate forecasts can enable retailer to improve their operational performance and profitability substantially by reducing lost sales, inventory levels and labor costs. READ MORE