Essays about: "Predictive Estimation"
Showing result 1 - 5 of 92 essays containing the words Predictive Estimation.
-
1. Using artificial intelligence to improvetime estimation for project management
University essay from Uppsala universitet/Signaler och systemAbstract : Time estimation is an important aspect in project management. Failure to make accurateestimates can lead to large consequences. Despite this, humans tend to make fairly inaccurateestimates when tasked to, often underestimating the time something will take substantially. READ MORE
-
2. Real-Time Certified MPC for a Nano Quadcopter
University essay from Linköpings universitet/Institutionen för systemteknikAbstract : There is a constant demand to use more advanced control methods in a wider field of applications. Model Predictive Control (MPC) is one such control method, based on recurrently solving an optimization problem for determining the optimal control signal. READ MORE
-
3. On Predicting Price Volatility from Limit Order Books
University essay from Uppsala universitet/Matematiska institutionenAbstract : Accurate forecasting of stock price movements is crucial for optimizing trade execution and mitigating risk in automated trading environments, especially when leveraging Limit Order Book (LOB) data. However, developing predictive models from LOB data presents substantial challenges due to its inherent complexities and high-frequency nature. READ MORE
-
4. Implementing SAE Techniques to Predict Global Spectacles Needs
University essay from Högskolan Dalarna/Institutionen för information och teknikAbstract : This study delves into the application of Small Area Estimation (SAE) techniques to enhance the accuracy of predicting global needs for assistive spectacles. By leveraging the power of SAE, the research undertakes a comprehensive exploration, employing arange of predictive models including Linear Regression (LR), Empirical Best Linear Unbiased Prediction (EBLUP), hglm (from R package) with Conditional Autoregressive (CAR), and Generalized Linear Mixed Models (GLMM). READ MORE
-
5. Dataset Drift in Radar Warning Receivers : Out-of-Distribution Detection for Radar Emitter Classification using an RNN-based Deep Ensemble
University essay from Uppsala universitet/Avdelningen för systemteknikAbstract : Changes to the signal environment of a radar warning receiver (RWR) over time through dataset drift can negatively affect a machine learning (ML) model, deployed for radar emitter classification (REC). The training data comes from a simulator at Saab AB, in the form of pulsed radar in a time-series. READ MORE