Search for dissertations about: "stochastic programming"
Showing result 1 - 5 of 87 swedish dissertations containing the words stochastic programming.
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1. Optimal bidding of a hydropower producer insequential power markets with riskassessment : Stochastic programming approach
Abstract : Short-term hydropower planning and bidding under uncertainty is a complicated task. The problem became more challenging with the liberalized market environment within the last two decades. READ MORE
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2. Decision Making under Uncertainty in Financial Markets : Improving Decisions with Stochastic Optimization
Abstract : This thesis addresses the topic of decision making under uncertainty, with particular focus on financial markets. The aim of this research is to support improved decisions in practice, and related to this, to advance our understanding of financial markets. READ MORE
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3. Approximation of Infinitely Divisible Random Variables with Application to the Simulation of Stochastic Processes
Abstract : This thesis consists of four papers A, B, C and D. Paper A and B treats the simulation of stochastic differential equations (SDEs). The research presented therein was triggered by the fact that there were not any efficient implementations of the higher order methods for simulating SDEs. READ MORE
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4. On Parameter Estimation and Control of Time-Varying Stochastic Systems
Abstract : This thesis is about parameter estimation and control of time-varying stochastic systems. It can be divided into two parts. The first part deals with an estimation algorithm commonly used when estimating parameters in time-varying stochastic systems, the Recursive Least Squares (RLS) algorithm with forgetting factor. READ MORE
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5. Language-Based Techniques and Stochastic Models for Automated Testing
Abstract : As software systems become bigger and scarier, automating their testing is crucial to ensure that our confidence in them can keep up with their growth. In this setting, Generational Fuzzing and Random Property-Based Testing are two sides of the same testing technique that can help us find bugs effectively without having to spend countless hours writing unit tests by hand. READ MORE