Sökning: "optimering modell"
Visar resultat 1 - 5 av 275 uppsatser innehållade orden optimering modell.
1. Optimizing Flight Ranking:A Machine Learning Approach : Applying Machine Learning to Upgrade Flight Sorting and User Experience
M1-uppsats, KTH/Hälsoinformatik och logistikSammanfattning : Flygresor.se, a leading flight comparison platform, uses machine learning to rankflights based on their likelihood of being clicked. The main goal of this project was toimprove this flight sorting to obtain a better user experience. The platform's existingmodel is based on a neural network approach and a limited set of features. LÄS MER
2. Robustness Analysis of Perfusion Parameter Calculations
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Cancer is one of the most common causes of death worldwide. When given optimal treatment, however, the risk of severe illness may greatly be reduced. Determining optimal treatment in turn requires evaluation of disease progression and response to potential, previous treatment. LÄS MER
3. Computationally Efficient Explainable AI: Bayesian Optimization for Computing Multiple Counterfactual Explanantions
Master-uppsats, KTH/Matematik (Avd.)Sammanfattning : In recent years, advanced machine learning (ML) models have revolutionized industries ranging from the healthcare sector to retail and E-commerce. However, these models have become increasingly complex, making it difficult for even domain experts to understand and retrace the model's decision-making process. LÄS MER
4. Optimering av flyghastighet för flygplan
Master-uppsats, KTH/Lättkonstruktioner, marina system, flyg- och rymdteknik, rörelsemekanikSammanfattning : Optimization of flight operations is a way to reduce the impact of aviation on the environment and make the use of airspace more effective. Reductions in fuel consumption and flight time are further desired by airlines to minimize operational costs. LÄS MER
5. Robust Portfolio Optimization with Correlation Penalties
Master-uppsats, KTH/Matematisk statistikSammanfattning : Robust portfolio optimization models attempt to address the standard optimization method's high sensitivity to noise in the parameter estimates, by taking an investor's uncertainty about the estimates into account when finding an optimal portfolio. In this thesis, we study robust variations of an extension of the mean-variance problem, where an additional term penalizing the portfolio's correlation with an exogenous return sequence is included in the objective. LÄS MER