Essays about: "monte carlo algorithm"
Showing result 6 - 10 of 165 essays containing the words monte carlo algorithm.
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6. Optimization of Radiotherapy Treatment Plans Based on Monte Carlo Dose Computations
University essay from Lunds universitet/Institutionen för reglerteknikAbstract : Treatment planning plays a vital role in providing good treatment to cancer patients. In order to reach an adequate treatment plan, the algorithm used for simulating the dose in the patient must model the reality well. READ MORE
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7. AI and real-time Strategy Games
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : As artificial intelligence continues to progress, applications hope to have AI perform tasks as good, if not better, than a human. A good way to test theoretical applications is through games, simple to complex. READ MORE
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8. Multi-factor approximation : An analysis and comparison ofMichael Pykhtin's paper “Multifactor adjustment”
University essay from Umeå universitet/Institutionen för matematik och matematisk statistikAbstract : The need to account for potential losses in rare events is of utmost importance for corporations operating in the financial sector. Common measurements for potential losses are Value at Risk and Expected Shortfall. These are measures of which the computation typically requires immense Monte Carlo simulations. READ MORE
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9. Reconstruction of Fire Spread with a Markov Random Field Mixture Model
University essay from Lunds universitet/Matematisk statistikAbstract : This thesis revolves around reconstructing fire sizes for historical fires in Jämtgaveln, Sweden based on data of fire scars in trees. We propose a Hidden Markov Model (HMM), where the domain is divided into quadratic grid cells of 250 $\times$ 250 m and with these grid cells we associate a binary Markov random field taking values 0 or 1 corresponding to no fire and fire respectively. READ MORE
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10. Analysing Regime-Switching and Cointegration with Hamiltonian Monte Carlo
University essay from Uppsala universitet/Statistiska institutionenAbstract : The statistical analysis of cointegration is crucial for inferring shared stochastic trends between variables and is an important area of Econometrics for analyzing long-term equilibriums in the economy. Bayesian inference of cointegration involves the identification of cointegrating vectors that are determined up to arbitrary linear combinations, for which the Gibbs sampler is often used to simulate draws from the posterior distribution. READ MORE