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Design of a Smart Algorithm Based on Two Dimensional Wavelet Transformation for Detection and Classification of Power Quality Disturbances
, M.Sc. Thesis Sharif University of Technology ; Mokhtari, Hossein (Supervisor)
Abstract
Power Quality can be simply defined as the quality of voltage at electrical loads. Detection and classification of voltage and current disturbances is of high importance in power system protection and monitoring. This procedure cannot be implemented by operators because of the high volume of the data which must be processed. So, it is needed to automate this procedure. Systems designed for this purpose usually contain three main parts: feature generation, feature selection and classifier design. The algorithms used for feature generation for power quality disturbances are mainly based on discrete Fourier transformation or discrete wavelet transformation. These approaches have shown some...
Using of Statistical and Machine Learning Methods in Financial Markets
, M.Sc. Thesis Sharif University of Technology ; Kianfar, Farhad (Supervisor)
Abstract
The problem of stock price direction prediction is of great value among investors and researchers in the past decades. Even the smallest improvement in the performance of forecasting methods can lead to noticeable profit for investors. In this regard, in this research, a new method for filling the literature gap in the field of stock price direction forecasting is proposed. In the proposed method, two concepts of dynamics and model selection in dealing with data is investigated. Finally a predictive model is developed according to the two abovementioned concepts. Moreover, in this work, using a meta-learning approach one step towards making the prediction process automatic is taken. The...