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Browsing M.S. Theses by Author "Baydoğan, Mustafa Gökçe."

Browsing M.S. Theses by Author "Baydoğan, Mustafa Gökçe."

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  • A column generation approach to solve ranking problems 
    Özcan, Erhan Can. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2020., 2020.)
    Many traditional classification approaches focus on the minimization of misclassification rate. However, this is not a suitable metric in case of imbalance in class distribution and unknown misclassification costs. In such ...
  • A data adaptive categorical time series representation for supervised learning 
    Çakın, Hande. (Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2016., 2016.)
    A vast majority of the studies in machine learning focus on time-directed or in other words sequential processes. Objectives of these studies vary from classi cation to prediction and clustering to segmentation. Since the ...
  • A methodology for determining the factors that increase artificial intelligence usage in mobile banking applications 
    Keçim, Gizem. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2019., 2019.)
    Recent developments in digital transformation (DT) and artificial intelligence transformation (AIT) are pushing businesses toward becoming intelligent enterprises. The banking is one of the affected businesses from this ...
  • A mixed-integer programming approach to example-dependent cost-sensitive learning 
    Temizöz, Tarkan. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2021., 2021.)
    In this research, we study example-dependent cost-sensitive learning that brings about varying costs/returns based on the labeling decisions. Originating from decisionmaking models, these problems are distinguished in areas ...
  • A new representation method for multivariate time series classification problem using interval means and polar histogram densities 
    Sergin, Nurettin Dorukhan. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2017., 2017.)
    Multivariate time series (MTS) classification is an instance of common time series data mining tasks and is ubiquitously found in many domains such as medicine, finance or human-computer interaction. Traditionally, the ...
  • Aggregation strategies for grid-based Numerical Weather Prediction (NWP) to improve power curve models with meta-learning extension 
    Konyar, Elif. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2021., 2021.)
    In the first part of this thesis, alternative strategies to estimate the wind power curve by utilizing grid-based weather forecasts from Numerical Weather Prediction (NWP) models are proposed. Traditional power curve ...
  • Algorithmic trading on cryptocurrency markets using machine learning techniques 
    Aktepe, Çağdaş. (Thesis (M.A.) - Bogazici University. Institute for Graduate Studies in the Social Sciences, 2018., 2018.)
    The aim of this thesis is to apply different machine learning models to the price prediction problem in cryptocurrency exchange markets in order to find profitable trading algorithm. Eight trading pairs are taken into ...
  • Autoregressive forests for multivariate time-series modeling 
    Tuncel, Kerem Sinan. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2017., 2017.)
    Multivariate Time Series (MTS) modeling has received significant attention in the last decade because of the complex nature of the data. Efficient representations are required to deal with the high dimensionality due to the ...
  • Data-driven operators for a hybrid evolutionary algorithm to solve multi-trip rich vehicle routing problem 
    Aykanat, Dilara. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2020., 2020.)
    Vehicle routing problems have been the subject of intensive research due to their di culty as a combinatorial optimization problem and their importance in real life operations. Heuristics are widely preferred to solve VRPs ...
  • Deep learning approaches for multi-site wind power forecasting in the West Aegean region of Turkey 
    Sarıkaya, Mert. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022)
    Wind energy is one of the most economical and promising ways of producing renewable energy among today's technologies. But the uncertainties arising from the chaotic nature and the variability of weather events are major ...
  • Ensemble - based shapelet approximation 
    Görgülü, Berk. (Thesis (M.A.) - Bogazici University. Institute for Graduate Studies in the Social Sciences, 2018., 2018.)
    Similarity search and classification on time series databases have received great interest over the past decade. The definition of similarity between the series is a major problem in this context. Nearest-neighbor (NN) ...
  • Forecasting with a large number of predictors :|a tree based moving average approach 
    Sel, Burakhan. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2020., 2020.)
    A large number of predictors brings valuable information to time series forecast ing problems, as well as difficulty in capturing this information. Short-term electricity load forecasting (STLF) problems are examples of ...
  • Learning nonlinear features to improve linear forecasting approaches 
    Öz, Mert. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2019., 2019.)
    Forecasting of future events is critical for decision making in many industries. Especially in the retail industry, forecasting of future sales has critical importance for management of the company. General time series ...
  • Modeling customers' online purchasing behavior using clickstream data 
    Yeşiladalı, Bahar. (Thesis (M.A.) - Bogazici University. Institute for Graduate Studies in the Social Sciences, 2018., 2018.)
    In the digitalizing world, the rapid development of the Internet has reshaped the customers’ expectations, attitudes and has also changed shopping habits. Visiting online stores for different reasons such as easier ...
  • nTreeClus: A model - basd partitioning clustering of sequential data 
    Jahanshahi, Hadi. (Thesis (M.A.) - Bogazici University. Institute for Graduate Studies in the Social Sciences, 2018., 2018.)
    The overwhelming presence of categorical/sequential data in diverse domains emphasizes the importance of sequence mining. The challenging nature of sequences proves the need for a continuing research to find a more accurate ...
  • Oblique random forest algorithm using lasso regression for wind power forecasting 
    Tabak, Burak. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022)
    With the increasing trend towards the use of renewable energy sources, wind power has been the subject of many researches. Wind power has stochastic nature due to uncertainties in atmospheric conditions, especially in wind ...
  • Pricing and order fulfillment for online marketplaces 
    Yıldız, Yasin. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2019., 2019.)
    The main purpose of this thesis is to provide a wholistic model for both pricing and order fulfillment problems of an online retailer. Real sales and shipment data of a company are used for both forecasting and fulfillment ...
  • Product ranking strategies for an online retailer 
    Güngör, Meriç. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2019., 2019.)
    Recommendation is one of the the most critical functionalities of an online retailer. Almost every platform wants to boost their sales by providing more relevant and personalized products for their consumer. The customer ...
  • Replenishment and lateral transshipment decisions in multi-period and multi-location inventory systems 
    Yıldız, Eda. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2021., 2021.)
    Inventory management has been researched for many years in the literature. The problem of determining the optimal inventory level directly affects the profitability of the systems. This thesis proposes an optimization ...
  • Short term electricity load forecasting using machine learning techniques 
    Yeşilyurt, Mustafa. (Thesis (M.A.) - Bogazici University. Institute for Graduate Studies in the Social Sciences, 2018., 2018.)
    Electricity is one of the most essential component of human life. Maintain ing and operating electric power systems is a complex task. Short term electricity load forecasting plays an important role in operation of electric ...

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