Sürdürülebilir Kalkınma Amaçları
Yayınlar
- MakaleAçık Erişim2020Machine learning and classical forecasting methods based decision support systems for covid-19
Ünlü, Ramazan; Namli, Ersin
From late 2019 to the present day, the coronavirus outbreak tragically affected the whole world and killed tens of thousands of people. Many countries have taken very stringent measures to alleviate the effects of the coronavirus disease 2019 (COVID-19) and are still being implemented. In this study, various machine learning techniques are implemented to predict possible confirmed cases and mortality numbers for the future. According to these models, we have tried to shed light on the future in terms of possible measures to be taken or updating the current measures. Support Vector Machines (SVM), Holt-Winters, Prophet, and Long-Short Term Memory (LSTM) forecasting models are applied to the novel COVID-19 dataset. According to the results, the Prophet model gives the lowest Root Mean Squared Error (RMSE) score compared to the other three models. Besides, according to this model, a projection for the future COVID-19 predictions of Turkey has been drawn and aimed to shape the current measures against the coronavirus.
- MakaleAçık Erişim2019A Comparative Study of Machine Learning and Linear Regression in Prediction of Pricing: A Case Study of Used Cars Price Prediction in Turkey
Ünlü, Ramazan E.; Gül, Ecem; Namli, Ersin
Used cars market is very buoyant in the World as well as in the Turkey and has a significant size. While sellers are looking for the maximum price for their vehicles, buyers are willing to buy a good quality vehicle with a minimum price. However, during the trading process various problems might occurred and even dealer might not have standard pricing policy for a specific vehicle. In this study, it is focused on whether a pricing policy for a used car can be created or not, collected real data, and applied methods based on statistics and artificial intelligence. As a subbranch of artificial intelligence, In addition to Machine learning’s success in complex problems such as natural language processing, text mining, image processing, it can also outperforms classical methods such as linear regression to solve regression problems. From this point, during this study Artificial Neural Networks, Support Vector Machines and Linear Regression methods are used and compared with the aim of standardizing used cars pricing. Based on the findings, it is possible to standardize used cars pricing with machine learning methods and chosen methods gives better results than classic linear regression method.