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dr Olgun Aydin
Employment
- Assistant professor at Katedra Statystyki i Ekonometrii
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total: 16
Catalog Publications
Year 2024
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Addressing the Weaknesses of Multi-Criteria Decision-Making Methods using Python
PublicationThe book aims to draw attention to the weaknesses in Multi-Criteria Decision-Making (MCDM) methods and provide insights to improve the decision-making process. By addressing these weaknesses, it seeks to enhance the accuracy and effectiveness of MCDM methods in selecting the best alternatives in various fields. The book covers popular MCDM methods such as TOPSIS, ELECTRE, VIKOR, and PROMETHEE. It compares traditional methods with...
Year 2023
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thestats: An Open-Data R Package for Exploring Turkish Higher Education Statistics
PublicationThere are open datasets available for official statistics, finance, education, and a variety of other domains. The open datasets are published by third-party vendors as well as official authorities. For example, The Turkish Higher Education Council maintains a web portal dedicated to higher education in Türkiye. Detailed datasets about universities, faculties, and departments can be obtained from the portal. Using the data provided...
Year 2022
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Analysing the Residential Market Using Self-Organizing Map
PublicationAlthough the residential property market has strong connections with various sectors, such as construction, logistics, and investment, it works through different dynamics than other markets; thus, it can be analysed from various perspectives. Researchers and investors are mostly interested in price trends, the impact of external factors on residential property prices, and price prediction. When analysing price trends, it is beneficial...
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Analyzing Wind Energy Potential Using Efficient Global Optimization: A Case Study for the City Gdańsk in Poland
PublicationWind energy (WE), which is one of the renewable energy (RE) sources for generating electricity, has been making a significant contribution to obtaining clean and green energy in recent years. Fitting an appropriate statistical distribution to the wind speed (WS) data is crucial in analyzing and estimating WE potential. Once the best suitable statistical distribution for WS data is determined, WE potential and potential yield could...
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The Conference Report of Why R? Turkey 2022: The First R Conference with Call For Papers in Turkey
PublicationWhy R? Turkey 2022 was a non-profit conference that aimed to bring Turkish R users together and encourage them to attend the R conferences. The targeted audience of the conference consisted of, data scientists, data analysts, and all R users from academia and industry. The three-day conference, which consisted of several events such as workshops, regular talks, lightning talks, short tutorials, and panels, was free of charge and...
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Using Long-Short term Memory networks with Genetic Algorithm to predict engine condition
PublicationPredictive maintenance (PdM) is a type of approach for maintenance processes, allowing maintenance actions to be managed depending on the machine's current condition. Maintenance is therefore carried out before failures occur. The approach doesn’t only help avoid abrupt failures but also helps lower maintenance cost and provides possibilities to manufacturers to manage maintenance budgets in a more efficient way. A new deep neural...
Year 2021
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Deep Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
Year 2020
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ANALYZING TITLES OF ECONOMY NEWS TO UNDERSTAND IMPACT OF COVID-19 ON ECONOMICAL SITUATION
PublicationCovid-19 affected the whole world in a short time, causing serious panic and uncertainty in society. Because it was an unprecedented disease, the medical community has worked hard to find out how to deal with it, and it continues to do so. The rapid spread of the disease, the shortage of hospital capacity and the increase in deaths drove the whole world to a closure, so to speak. In this time period, life in the world came to a...
Year 2019
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Decision making process using deep learning
PublicationEndüstri 4.0, dördüncü endüstri devrimi veya Endüstriyel Nesnelerin İnterneti (IIoT) olarak adlandırılan sanayi akımı, işletmelere, daha verimli, daha büyük bir esneklikle, daha güvenli ve daha çevre dostu bir şekilde üretim yapma imkanı sunmaktadır. Nesnelerin İnterneti ile bağlantılı yeni teknoloji ve hizmetler birçok endüstriyel uygulamada devrim niteliği taşımaktadır. Fabrikalardaki otomasyon, tahminleyici bakım (PdM – Predictive...
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Design of dimensionally stable composites using efficient global optimization method
PublicationDimensionally stable material design is an important issue for space structures such as space laser communication systems, telescopes, and satellites. Suitably designed composite materials for this purpose can meet the functional and structural requirements. In this paper, it is aimed to design the dimensionally stable laminated composites by using efficient global optimization method. For this purpose, the composite plate optimization...
Year 2018
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Estimation of Housing Demand with Adaptive Neuro-Fuzzy Inference Systems (ANFIS)
PublicationIt has always been important to anticipate the demand for a product. To determine the demand for any product, the parameters such as the economic situation and the demands of the rival products are used generally. Especially in the housing sector, which is the locomotive sector for emerging countries, it is critical to anticipate housing demand and its relationship with economic variables. Because of that, economists, real estate...
Year 2017
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Count Data Modeling About Relationship Between Dubai Housing Sales Transactions and Financial Indicators
PublicationIn this study, illustrating and comparing the performances of count data models such as Poisson, negative binomial (NB), Hurdle and zero-inflated models for the determination of factors affected housing sales in Dubai. Model comparisons are made via Akaike’s information criterion (AIC), the Vuong test and examining the residuals. Main purpose of this study is building reliable statistical model for relationship between Dubai housing...
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Real estate investment trusts in Turkey: Structure, analysis, and strategy
PublicationPurpose-Aim of this study is to make the determinations related to the problems mentioned in the REIT sector in Turkey, to offer a solution for this issue, and to ensure the classification in the sector by adhering to the financial data of the REITsMethodology-Financial data set of the REITs was firstly standardized by using median instead of mean. Then, the scoring was performed according to defined coefficients....
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Using LSTM networks to predict engine condition on large scale data processing framework
PublicationAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
Year 2016
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Modelling of residential sales price with kriging using different distance metrics in different correlation functions
PublicationThe modelling and estimation of sales prices based on economical conditions are important for housing sector especially in developing countries. Analysts are focused on the subject to analyze price movements and estimate the future trend of the sales prices for housing sector. In this study, we tried to generate a robust and efficient model related to the subject. Firstly, we investigated economic variables affecting housing sales...
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