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Visar resultat 1 - 5 av 63 uppsatser som matchar ovanstående sökkriterier.

1. 1. Robust Non-Linear State Estimation for Underwater Acoustic Localization : Expanding on Gaussian Mixture Methods

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

   Författare :Diogo Antunes; [2023]
   Nyckelord :Robust state estimation; Underwater localization; Target tracking; Gaussian mixture; AUV; Estimação robusta de estado; Localização subaquática; Rastreamento de alvos; Mistura Gaussiana; AUV; Robust tillståndsuppskattning; Undervattenslokalisering; Målspårning; Gaussisk blandning; AUV;

   Sammanfattning : Robust state estimation solutions must deal with faulty measurements, called outliers, and unknown data associations, which lead to multiple feasible hypotheses. Take, for instance, the scenario of tracking two indistinguishable targets based on position measurements, where each measurement could refer to either of the targets or even be a faulty reading. LÄS MER

3. 2. Exploring the Feasibility of Replicating SPAN-Model's Required Initial Margin Calculations using Machine Learning : A Master Thesis Project for Intraday Margin Call Investigation in the Commodities Market

   Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Clara Branestam; Amanda Sandgren; [2023]
   Nyckelord :Machine Learning; Market Risk; Initial Margin; SPAN-model; Central Counterparty Clearing; Margin Call;

   Sammanfattning : Machine learning is a rapidly growing field within artificial intelligence that an increasing number of individuals and corporations are beginning to utilize. In recent times, the financial sector has also started to recognize the potential of these techniques and methods. LÄS MER

4. 3. Multi-scale Bark Beetle Predictions Using Machine Learning

   Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

   Författare :Albert Øhrman Wellendorf; [2023]
   Nyckelord :Geography; GIS; Geographically weighted regression; bark beetle; machine learning; Earth and Environmental Sciences;

   Sammanfattning : Bark beetle attacks have led to widespread tree disturbance and deaths in many parts of the world, and thereby also economic and biodiversity losses. Forest-rich Sweden has experienced periodic attacks, latest in 2018. LÄS MER

5. 4. Prognostics for Condition Based Maintenance of Electrical Control Units Using On-Board Sensors and Machine Learning

   Master-uppsats, Linköpings universitet/Fordonssystem

   Författare :Gabriel Fredriksson; [2022]
   Nyckelord :machine learning; random forest; random survival forest; condition based maintenance; cbm; reliability; solder joint failure; thermomechanical cycling; ECU; lifetime prediction; data-driven; statistics; BGA; PCBA; field quality; maintenance; truck; bus; vehicle;

   Sammanfattning : In this thesis it has been studied how operational and workshop data can be used to improve the handling of field quality (FQ) issues for electronic units. This was done by analysing how failure rates can be predicted, how failure mechanisms can be detected and how data-based lifetime models could be developed. LÄS MER

7. 5. Risk measurement of cryptocurrencies using value at risk and expected shortfall

   Magister-uppsats, Lunds universitet/Nationalekonomiska institutionen

   Författare :Van Cao Thi Hong; [2022]
   Nyckelord :cryptocurrencies; value at risk; expected shortfall; risk measurement; parametric methods; non-parametric methods; EWMA; GARCH; EGARCH; GJRGARCH; backtesting; Business and Economics;

   Sammanfattning : Cryptocurrencies are highly volatile and risky assets, therefore, it is of vital importance to find an appropriate model for risk measurement. This thesis compares three parametric and three non-parametric estimation methods to estimate the value at risk and the expected shortfall of five cryptocurrencies, namely Bitcoin (BTC), Ethereum (ETH), Binance coin (BNB), Ripple coin (XRP), and Cardano (ADA). LÄS MER