Browsing by Subject "Machine learning"
Now showing items 1-20 of 24
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A Computationally Efficient Heuristic Algorithm For Piecewise Linear Regression
(Fen Bilimleri Enstitüsü, 2023)Regression analysis is a method used to model the relationship between the dependent variables and the independent variable in the data, and to predict the dependent variable from the independent variables in the future ... -
A Hybrid and Reliable Method Integrating Depth and Technical Analysis with Machine Learning Techniques for Predicting Stock Prices
(Fen Bilimleri Enstitüsü, 2019)It is quite complicated and difficult to predict the price changes direction of stock, because of the price changes of stock are non-linear. Some statistical methods are used to estimate these price changes direction, but ... -
A Machıne Learnıng Approach For The Detectıon Of Trade Based Manıpulatıons In Borsa İstanbul
(Fen Bilimleri Enstitüsü, 2022)Capital markets, one of the pillars of the financial system, play a vital role in transferring the excess funds of savers to investors who need funds in the medium and long term. Trust is essential for the safe and effective ... -
A Q-learning Based Load Balanced and QoS-aware SDN Approach: A Case Study in Defence Industry
(Fen Bilimleri Enstitüsü, 2022)Traditional network routing methods are insufficient in the face of exponentially increasing data, device diversity and service demands' variety, making the necessity of more manageable routing methods felt at both the ... -
Advancing Software Defect Prediction through Ensemble XAI Methods: Insights and Performance Evaluation
(Fen Bilimleri Enstitüsü, 2024-05)This doctoral thesis presents a comprehensive investigation into enhancing the interpretability and transparency of Machine Learning (ML) models in the domain of Software Defect Prediction (SDP) through Model-Agnostic ... -
An Approach for Multi-Hazard Susceptibility Assessment For Landslides, Earthquakes And Floods
(Fen Bilimleri Enstitüsü, 2023-03-29)Production of precise and up-to-date susceptibility maps at regional level is essential for mitigating disasters, selecting new sites for settlements and construction, and planning in areas prone to various natural hazards. ... -
An Enhanced Approach for Malware Detectıon By Utılızıng Computer Vısıon and Memory Forensıc
(Fen Bilimleri Enstitüsü, 2020)The number of advanced malware, which have been released, has increased substantially year after year with the increase in the use of information systems. Due to the ransomware programs, which we have frequently heard ... -
Artificial Intelligence Applications in Early Diagnosis of Sepsis Disease
(Fen Bilimleri Enstitüsü, 2023)Sepsis is a major cause of death in intensive care units worldwide. Early diagnosis and treatment are crucial for improving patient survival and reducing organ dysfunction. Combining sepsis research and computer science ... -
Assessment of Machine Learning Methods for Mass Real Estate Appraisal
(Fen Bilimleri Enstitüsü, 2022)In this thesis, the use of machine learning (ML) approaches for the purpose of real estate mass appraisal was investigated using five different methods in a large area considering the efficiency, accuracy, and transparency. ... -
Combınatorıal Solutıons For Consensus Algorıthms And Blockchaın Shardıng
(Fen Bilimleri Enstitüsü, 2021)The scalability problem in blockchain technology seems to be the essential issue to be solved. It is known that the choice of a compromised algorithm is critical for the practical solution of this important problem. Usually, ... -
Constructıng Tradıng Strategıes Usıng Artıfıcıal Intellıgence Based Models: An Applıcatıon For Borsa Istanbul
(Sosyal Bilimler Enstitüsü, 2020)The aim of this thesis is to test the Efficient Market Hypothesis using artificial intelligence-based techniques. In this regard, we utilize artificial intelligence based models that have both deep and shallow architectures ... -
Detecting Novel Behavior and Process Improvement with Multi-Modal Process Mining
(Fen Bilimleri Enstitüsü, 2024)The importance of data has increased, especially with the spread of Internet of Things (IoT)-like technologies as a result of the 4th Industrial Revolution. In order to make sense of the data, valuable sciences have also ... -
Determining Cutoff Point of Ensemble Trees Based on Sample Size In Predicting Clinical Dose With Dna Microarray Data
(Hindawi Ltd, 2016)Background/Aim. Evaluating the success of dose prediction based on genetic or clinical data has substantially advanced recently. The aim of this study is to predict various clinical dose values from DNA gene expression ... -
Development of A Deep Learning Approach for 3Dimensional Point Cloud Classification
(Fen Bilimleri Enstitüsü, 2024-09)3D point cloud classification is a crucial step in point cloud processing, as it serves as the foundation for subsequent processes that rely on the classification results. With the increasing volume of 3D point cloud ... -
Development of A Machine Learning Based Application For Diagnosing Autoinflammatory Diseases
(Fen Bilimleri Enstitüsü, 2024-02)Diseases caused by immune system dysfunction have numerous complications, significantly affecting patients' life quality. One specific group of such diseases is autoinflammatory diseases, which occur when the immune system ... -
Gmdh2: Binary Classification Via Gmdh-Type Neural Network Algorithms-R Package And Web-Based Tool
(2019)Group method of data handling (GMDH)-type neural network algorithms are the self-organizing algorithms for modeling complex systems. GMDH algorithms are used for different objectives; examples include regression, classification, ... -
Improving Video Retrieval with Data Expansion and Knowledge Graphs
(Fen Bilimleri Enstitüsü, 2024)Recent video-text multimodel approaches provide good results on retrieval tasks. However, the performance of domain-specific cases might be decreased because of internal differences with generic data. Since deep learning ... -
Large-Scale Arabic Sentiment Corpus And Lexicon Building For Concept-Based Sentiment Analysis Systems
(Fen Bilimleri Enstitüsü, 2018)Within computer-based technologies, the usage of collected data and its size are continuously on a rise. This continuously growing big data processing and computational requirements introduce new challenges, especially ... -
Machine Learning-Adapted Rapid Visual Screening Method For Prioritizing Seismic Risk States of Masonry Structures
(Fen Bilimleri Enstitüsü, 2023-12-30)The majority of earthquake-related losses are associated with fully collapsed buildings. So, the determination of the seismic risk of buildings is essential for building occupants located in active earthquake zones. ... -
Predicting Disease-Gene Associations Via Machine Learning
(Bilişim Enstitüsü, 2024)In the quest to elucidate disease etiology and develop advanced diagnostic and treatment tools, knowing disease-gene relationships is of great importance. Traditional approaches based on manual curation fall short due ...
