Yazar "Efe, Omer Faruk" seçeneğine göre listele

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    Application of Multi-Criteria Decision-Making Methods for the Underground Mining Method Selection
    (IGI Global, 2023) Mijalkovski, Stojance; Efe, Omer Faruk; Zeqiri, Kemajl
    In mining, there are many complex problems that need to be solved in a limited period of time. When solving these complex tasks, it is necessary to take into account many parameters, all in order to determine the optimal solution for a given problem. The application of multi-criteria decision-making methods (MCDM) is very widely used to solve such complex problems. One of the most complex problems in mining is the underground mining method selection. In order to choose the most appropriate method of mining excavation, it is necessary to take into account a large number of influential parameters according to which we will compare mining methods. This paper will discuss the problem of underground mining method selection using the EDAS method. Also, a comparison of the obtained results will be made for a specific example, when applying several methods for multi-criteria decision-making. After comparing the obtained results, the most suitable mining method for a specific example will be determined. © 2023, IGI Global.
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    Lean Transformation Practices in Healthcare
    (IGI Global, 2025) Efe, Omer Faruk; Nal, Mustafa
    This study investigates the benefits of adopting lean management in the healthcare sector, focusing on its impact on hospital management, employees, and patients. By advocating for the widespread implementation of lean management practices, this research aims to contribute to the healthcare management literature, emphasizing its role in enhancing communication and operational efficiency. The study was conducted in a public hospital in Turkey, with data collected between July 16, 2022, and January 31, 2023. A Value Stream Mapping (VSM) approach was employed to analyze the existing workflow and develop a "current state" map. Subsequently, lean transformation principles were applied to design a "future state" map, providing insights into potential process improvements. The findings culminate in a set of recommendations aimed at optimizing operational efficiency and strengthening communication within healthcare settings. © 2026, IGI Global Scientific Publishing. All rights reserved.
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    Multiple Time Series Analysis with LSTM
    (Springer Science and Business Media Deutschland GmbH, 2024) Şen, Hasan; Efe, Omer Faruk
    Inflation is caused by the growing gap between the amount of money actively involved and the sum of products and services available for purchase. It is an economic and monetary process that manifests itself as a constant rise in prices, a fall in the current value of money. Inflation is a subject that keeps itself constantly updated in our country and around the world. The main purpose of the central banks, which are dependent on countries in the world and continue their activities, on the economy is to ensure price stability permanently. In recent years, artificial intelligence techniques have been used more and more in order to consistently predict the value of inflation in the future and to make future studies with the forecasts obtained. The aim of this study is to estimate inflation in the Turkish economy with time series analysis by using LSTM (Long Short Term Memory) model, which is one of the artificial neural networks types, on a python computer program. With this study, the estimation made by the LSTM model showed result when compared in terms of MAPE and MSE statistical analyses. It has been observed that the irregular increase in the inflation value within the country in the recent periods directly affects the success level of the models. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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    Regional Guidance System for Cleaning Robots as a Result of Pollution of Solar Panels
    (ISRES Organizasyon Turizm Eğitim Danışmanlık Ltd. Şti., 2023) Cantez, Emin; Sahın, Hasan; Efe, Omer Faruk
    Solar energy production is provided by thermal and photovoltaic (PV) systems. Among them, PVs are considered one of the most important power generation systems that produce safe and sustainable energy. Depending on the outdoor conditions, PV systems get dirty over time due to dust, rain and environmental factors. Above the PV system When polluted, it causes a significant decrease in their efficiency. Especially in large photovoltaic power plants, it is seen that the panels are not polluted equally. But the cleaning robots system When it starts to clean, it cleans all the panels. Cleaning all clean and dirty panels causes energy consumption, material life and spare parts waste. In the system we have planned, it is planned to clean the panels by detecting the dirty panels with the camera and directing the cleaning robot only to the contaminated areas. Since only the contaminated areas will be cleaned, the energy production efficiency of the panels will increase and the cleaning time will be shortened.