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shokuhian--hamideh
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Short-term Load Forecasting
, M.Sc. Thesis Sharif University of Technology ; Fatemi Ardestani, Farshad (Supervisor) ; Barakchian, Mahdi (Supervisor)
Abstract
In this thesis we are going to forecast the hourly consumption of the electricity over the country with two models and then, combine them. The first model decomposes the consumption to a deterministic trend and a stochastic residual. The second one assumes that the trend part is also stochastic.Once the consumption is being predicted separately by the models, in the second part of the thesis, we will combine the results to get a final prediction. This prediction is going to be compared with the load forecast of the Dispatching Unit of the electricity network as a base model. We are going to answer two important questions: firstly, does combining the models give a better prediction or not,...
Generalization of the Online Prediction Problem Based on Expert Advice
, M.Sc. Thesis Sharif University of Technology ; Foroughmand Araabi, Mohammad Hadi (Supervisor) ; Alishahi, Kasra (Co-Supervisor) ; Hosseinzadeh Sereshki, Hamideh (Co-Supervisor)
Abstract
One of the most important problems in online learning is a prediction with expert advice. In each step we make our prediction not only based on previous observation but also use expert information. In this thesis, we study the different well-known algorithms of expert advice and generalize problems when data arrival is in the two-dimensional grid. regret is a well-studied concept to evaluate online learning algorithm. online algorithm when data arrive consecutively in T time step has regret O (√(T)) . regret in two-dimensional grid with T row and P column is O(T√(P)).
2010 MSC: 68Q32 ; 68T05 ; 90C27
2010 MSC: 68Q32 ; 68T05 ; 90C27