Yıkanmış Türk Linyit Kömürlerinin Üst Isıl Değerinin Destek Vektör Regresyonu ile Tahmini

Acikkar, M.; Sivrikaya, Osman

doi:10.31590/ejosat.642676

Cited by 4 publications

(3 citation statements)

References 39 publications

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“…Predictive models are compared to performance measurements. For GCV estimation, all models indicate that the SVR-based model is better than ANN-based models and THE RBFN-based model performs better than MLP and GRNN-based models [9].…”

Section: Introductionmentioning

confidence: 97%

“…It has been concluded that CO2 emissions have travelled on a yacht over the years [8]. Açıkkar et al (2020) the upper thermal value of Turkish lignite charcoal washed in its work (GCV) was estimated using machine learning methods and dry basic short analysis results of coal samples. In addition, they implemented three different Artificial Neural Networks (ANN) in their work, including Support Vector Regression (SVR) and Multilayer Sensor (MLP), General Regression Neural Network (GRNN), and radiant-based function Neural Network (RBFN), and GCV estimation models.…”

Section: Introductionmentioning

confidence: 99%

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Estimating CO2 Emission Time Series with Support Vector Machines Regression, Artificial Neural Networks, and Classic Time Series Analysis

Çemrek

Gunes

2021

Turkish Journal of Forecasting

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Artificial intelligence machine learning has become very popular in recent years. It offers the ability to combine machine learning theory with many analyses such as classification, prediction models, natural language processing. Carbon dioxide emission is defined as the release of carbon, often caused by human nature, into the atmosphere. In the 19 th century, the industrial revolution took place and the use of coal-powered industrial vehicles increased the amount of carbon released into the atmosphere. These gases released into the atmosphere have brought climate problems in proportion to the increase in temperature. Because of climate problems, the sweet water source of the earth's ice pack continues to melt and the sea level rises. Therefore, the amount of carbon dioxide emission (metric tons per person) Artificial Neural Networks (ANN), Support Vector Machines Regression (SVMR), estimated by Box-Jenkins technique based on time series analysis and estimated estimates compared to MSE (mean square error) between 1990-2018. The comparison found that the Artificial Neural Networks have better predictive results on the SVMR and Box-Jenkins technique on the performance benchmark.

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Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Estimating CO2 Emission Time Series with Support Vector Machines Regression, Artificial Neural Networks, and Classic Time Series Analysis

Çemrek

Gunes

2021

Turkish Journal of Forecasting

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“…Therefore, it is necessary to reduce SO2 at its source before releasing it into the atmosphere (Acar et al, 2018). Low-quality coals are used by passing through certain stages to minimize environmental damage and because they are not suitable for direct use (Açıkkar and Sivrikaya, 2020). Since coals in our country are generally lignite coal with low calorific value, their evaluation for electricity generation purposes is more appropriate.…”

Section: Introductionmentioning

confidence: 99%

The Oxy-Fuel Combustion Power Plant Model with Desulphurization Process and The Effect of Different Types of Coal on Operating Parameters

Erbaş¹,

Arat²

2021

European Journal of Science and Technology

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Clean coal technologies are defined as applications that improve environmental acceptability and efficiency in producing, preparing and using coal. With clean coal technologies, it is possible to increase the amount of energy obtained per unit ton by reducing emissions and wastes. However, today there are strict sanctions that must be followed due to the legal regulations on the protection of the environment and combating climate change. At this point, the clean coal-burning technologies in which the oxy-fuel combustion process (with the possibility of CO2 storage) takes place come to the fore. In this study, the method of burning fuel with oxygen in a thermal power plant with a gross electricity generation of 500 MW was discussed. This thermal power plant model also has a fluidized bed dryer, a desulphurization plant, and a CO2 storage process. The combustion results of different properties of coals were examined, and their effect on operating parameters was investigated.

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Şirket Değerlemesinde Makine Öğrenmesi Algoritmalarının Kullanımına Yönelik Bir Uygulama: Holding Şirketleri Örneği

Şeyranlıoğlu,

Karavardar

2024

Uluslararası Ekonomi Ve Yenilik Dergisi

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Bu araştırmanın amacı, şirket değerini etkileyen unsurların tespit edilmesi, bu unsurlardan hareketle finansal oranlar/veriler kullanılarak Türkiye’de Borsa İstanbul Yatırım ve Holding Endeksi’nde (BİST XHOLD) işlem gören holding şirketlerinin şirket değerlerini tahmin etme aracı olarak makine öğrenimi algoritmalarından Yapay Sinir Ağları (YSA), Destek Vektör Makineleri (DVM), Karar Ağaçları (KA) ve Rastgele Orman (RO) ile uygulanabilirliğini ortaya koymaktır. Belirtilen algoritmalar ile dört adet model kurulmuş ve bu modellerin tahmin gücü sınanmıştır. Bulgulara göre piyasa değerini R2, MAE ve RMSE ölçütleri baz alınarak YSA algoritmasının daha güçlü tahmin ürettiği görülmüştür. Bu araştırma ile şirket değerinin tahminine ve gelecek fiyatların öngörüsüne yönelik literatür incelenmiş, finansal oranlar/verileri içeren bütüncül bir yapı ortaya koyularak, yatırımcılara ve analistlere hisse senedi yatırımlarında ve şirket değerleme süreçlerinde makine öğrenimi algoritmaları ile geleneksel değerleme yaklaşımlarına kıyasla farklı bir bakış açısı sunulmuştur.

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Yıkanmış Türk Linyit Kömürlerinin Üst Isıl Değerinin Destek Vektör Regresyonu ile Tahmini

Cited by 4 publications

References 39 publications

Estimating CO2 Emission Time Series with Support Vector Machines Regression, Artificial Neural Networks, and Classic Time Series Analysis

Estimating CO2 Emission Time Series with Support Vector Machines Regression, Artificial Neural Networks, and Classic Time Series Analysis

The Oxy-Fuel Combustion Power Plant Model with Desulphurization Process and The Effect of Different Types of Coal on Operating Parameters

Şirket Değerlemesinde Makine Öğrenmesi Algoritmalarının Kullanımına Yönelik Bir Uygulama: Holding Şirketleri Örneği

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