Yazarlar
- Can, Erol(29)
- Kumbasaroglu, Atila(17)
- Yalciner, Hakan(17)
- Bayata, Halim Ferit(14)
- Ting, Naim Suleyman(14)
- Katipoğlu, Okan Mert(13)
- Bayrak, Osman Ünsal(12)
- Sahin, Yakup(12)
- Turan, Ahmet İhsan(9)
- Baş, Fatih İrfan(8)
- Destek, Mehmet Akif(8)
- Manga, Müge(8)
- Çolak, Muhammed Ali(8)
- Bulut, H. Alperen(6)
- Manga, Muge(6)
- Tastimur, Canan(6)
- Akin, Erhan(5)
- Akoğuz, Harun(5)
- Akın, Fatih(5)
- Balli, Esra(5)
- Dede, Tayfun(5)
- Sarıgöl, Metin(5)
- Sarıçiçek, İnci(5)
- Aka, Salih(4)
- Ayasun, Saffet(4)
- Ayaz, Yaşar(4)
- Celik, Alper(4)
- Demirci, Oğuz Kürşat(4)
- Demirel, Soner(4)
- Kalkan, Orhan(4)
- Keleş, Ömer Faruk(4)
- Tortum, Ahmet(4)
- Tuysuz, Suat(4)
- Yavuz, Selahattin(4)
- Yazici, Ahmet(4)
- Yazıcı, Ahmet(4)
- Yesilyurt, Huseyin(4)
- Yılmaz, Mehmet(4)
- Çabuk, Umut Can(4)
- Özkan, Kemal(4)
Yayınlar
- ArticleYalnız künye2023Evaluation of the performance of data-driven approaches for filling monthly precipitation gaps in a semi-arid climate conditions
Katipoğlu, Okan Mert
Missing data cause problems in meteorological, hydrological, and climate analysis. The observation data should be complete and cover long periods to make the research more accurate and reliable. Artificial intelligence techniques have attracted interest for completing incomplete meteorological data in recent years. In this study the abilities of machine learning models, artificial neural networks, the nonlinear autoregressive with exogenous input (NARX) model, support vector regression, Gaussian processes regression, boosted tree, bagged tree (BAT), and linear regression to fill in missing precipitation data were investigated. In developing the machine learning model, 70% of the dataset was used for training, 15% for testing, and 15% for validation. The Bayburt, Tercan, and Zara precipitation stations, which are closest to the Erzincan station and have the highest correlation coefficients, were used to fill the data gaps. The accuracy of the constructed models was tested using various statistical criteria, such as root-mean-square error (RMSE), mean absolute error (MAE), Nash–Sutcliffe model efficiency coefficient (NSE), and determination coefficient (R2) and graphical approaches such as scattering, box plots, violin plots, and Taylor diagrams. Based on the comparison of model results, it was concluded that the BAT model with R2: 0.79 and NSE: 0.79 and error (RMSE: 11.42, and MAE: 7.93) was the most successful in the completion of missing monthly precipitation data. The contribution of this research is assist in the choice of the best and most accurate method for estimating precipitation data in semi-arid regions like Erzincan.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2023Mobile-DenseNet: Detection of building concrete surface cracks using a new fusion technique based on deep learning
Akgül, İsmail
Crack detection is very important during the inspection of building structures to determine whether they are safe. Therefore, to ensure the reliability and longevity of buildings, it is necessary to have experts periodically carry out building inspections. Building inspection has traditionally been conducted using human-based visual inspection methods as well as artificial intelligence methods that have shown great success in computer vision in recent years. In this study, 9 different models (Xception, VGG16, ResNet101, InceptionV3, InceptionResNetV2, MobileNetV2, DenseNet169, NASNetMobile, and EfficientNetB6), which have shown significant success in the field of artificial intelligence, are discussed to detect and classify cracks in building structures. In addition, a new fusion model structure called Mobile-DenseNet has been proposed by making block cutting and adding auxiliary layers to the MobileNetV2 and DenseNet169 model structures. With this proposed model structure, cracks in concrete structures were classified. A dataset consisting of concrete surface images was used to detect and classify cracks occurring in concrete structures, and a 99.87 % success rate was achieved with the proposed Mobile-DenseNet model in classifying cracks occurring on the concrete surface. The proposed model outperformed the traditional pretrained model structures in the study in terms of the number of transactions, density, features, complexity, and success accuracy.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2023Boosting flood routing prediction performance through a hybrid approach using empirical mode decomposition and neural networks: a case study of the Mera River in Ankara
KatipoğLu, Okan Mert; Sarıgöl, Metin
Flood routing is vital in helping to reduce the impact of floods on people and communities by allowing timely and appropriate responses. In this study, the empirical mode decomposition (EMD) signal decomposition technique is combined with cascade forward backpropagation neural network (CFBNN) and feed-forward backpropagation neural network (FFBNN) machine learning (ML) techniques to model 2014 floods in Ankara, Mera River. The data are split in order to avoid the underfitting and overfitting problems of the algorithm. While establishing the algorithm, 70% of the data were divided into training, 15% testing and 15% validation. Graphical indicators and statistical parameters were used for the analysis of model performance. As a result, the EMD signal decomposition technique has been found to improve the performance of ML models. In addition, the EMD-FFBNN hybrid model showed the most accurate estimation results in the flood routing calculation. The study’s outputs can assist in designing flood control structures such as levees and dams to help reduce flood risk.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2022BIST-100 Endeks Hareketlerinin BRICS Endeksleri Aracılığıyla Tahmin Edilmesi: Yapay Sinir Ağları Uygulaması
Sarı, Sali̇m Sercan; Ilgın, Kübra Saka
Bu çalışmada, BİST 100 endeks hareketlerinin BRICS ülkelerinin gösterge endeksleri ile tahmin edilmesi amaçlanmaktadır. Çalışmanın uygulama kısmında, tahmin için geliştirilen modellerde bağımlı değişken olarak BİST 100 endeksinin aylık kapanış fiyatları, bağımsız değişken olarak BRICS ülkelerinin gösterge endekslerinin aylık kapanış fiyatları kullanılmıştır. Bu kapsamda 5’i bağımsız, 1’i bağımlı değişken olmak üzere toplam 6 değişkenle kurulan 20 model Yapay Sinir Ağları (YSA) yöntemi ile analiz edilmiştir. Analizi yapılan tüm modellerde, 2008- 2019 yılları arasındaki aylık verilerden yararlanılmıştır. Değişkenlere ait toplanan 143 aylık verinin %70’i eğitim verisi olarak, %30’u ise matematiksel modellerin tahmin başarısını ölçmek için kullanılmıştır. Elde edilen bulgulara göre, Yapay Sinir Ağları (YSA) yöntemi ile BİST 100 endeksini tahmin etmek için kurulan modellerin BRICS ülkelerinden sırasıyla Hindistan, Güney Afrika ve Rusya ülkeleri için başarılı sonuçlar verdiği gözlenmiştir.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2022Regional Determinants and Spatial Differentiation of Innovation in Turkey
Tuysuz, Suat; Altuğ, Fatih
This study investigates the spatial distribution and regional determinants of innovation in Turkey. In this study, we applied regression analysis which is called global (GR) and geographically weighted regression (GWR). The empirical analyses show that human capital as an internal resource and export as an external resource/openness are the determinants of innovation in the Turkish case. GWR showed that these predictors do not affect innovation in every region. Our method differentiates us from other studies in the literature. The research depicted an important image reflecting the policymakers' urging to take the local and regional dynamics into account and their top-down policies on innovation. The present study proves empirically that place-based approaches are needed in innovation policy.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2022Tedarik Zinciri Entegrasyonu ve Dijitalleşmenin Performansa Etkisi: Alıcı-Tedarikçi Risk Yönetiminin Aracılık Rolü
Oğuz, Alparslan; Perçin, Selçuk
Çalışmanın amacı, tedarik zinciri entegrasyonu ve dijitalleşmenin performansa etkisinde tedarik zinciri risk yönetiminin aracı rolünü belirlemektir. Bunun için yapısal bir model oluşturulmuştur. Yapısal modelde yer alan ilişkiler, Gaziantep Organize Sanayi Bölgelerinde faaliyet gösteren 246 üretim işletmesinden elde edilen veriler ile analiz edilmiştir. Modelde yer alan ilişkilerin belirlenmesinde Yapısal Eşitlik Modeli yöntemi kullanılmıştır. Analiz sonucunda, alıcı-tedarikçi entegrasyonu, dijitalleşme ve alıcı-tedarikçi risk yönetimi faktörlerinin işletme performansı üzerinde anlamlı bir etkiye sahip olduğu belirlenmiştir. Ayrıca, alıcı-tedarikçi entegrasyonu ve dijitalleşmenin, alıcı-tedarikçi risk yönetimi üzerinde anlamlı etkisi olduğu belirlenmiştir. Çalışmada, aracı etkilerde araştırılmıştır. Buna göre, alıcı-tedarikçi entegrasyonu ve dijitalleşmenin işletme performansına etkisinde alıcı-tedarikçi risk yönetiminin kısmi aracılık etkisi bulunmaktadır. Sonuçlar, yapısal modeli desteklemektedir. Elde edilen sonuçların literatüre, işletmelere ve yöneticilere çeşitli katkılar sağlayabileceği ifade edilebilir.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2022Hava kargo taşıyıcılarının kargo uçağı tipi seçiminde stratejık karar verme
Tanrıverdi, Gökhan; Lezki, Şenay; Doğan, Ümit
Kargo uçağı tipi seçimi, özellikle bir kargo uçağının satın alınması halinde ciddi bir mali yük oluşturduğundan hava kargo taşıyıcılarının ekonomik sürdürülebilirliğini etkileyen stratejik kararlardan biridir. Bu bağlamda çalışmanın amacı, hava kargo taşıyıcılarının iş modellerine göre en iyi kargo uçağı tipini belirlemelerine yardımcı olacak bir metodoloji ortaya koymaktır. Çalışmada, literatürden ve uzmanlardan toplanan nitel ve nicel kriterler kullanılmaktadır. Kriter ağırlıklarını belirlemek için AHP tekniği kullanılmıştır. En iyi alternatif kargo uçağı tipini seçmek için ise TOPSIS ve VIKOR tekniklerinden faydalanılmıştır. Bulgular, sektör geneli için A330-200F ve B777F kargo uçağı tiplerinin en iyi iki kargo uçağı tipi olduğunu göstermektedir.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2022Post-fire Seismic Behavior of RC Columns Built with Sustainable Concrete
Demir, Ugur; Unal, Goktug; Goksu, Caglar; Saribas, Ilyas; Ilki, Alper
In this study, four full-scale reinforced concrete columns were built replacing 50% of natural coarse aggregates in concrete mix by recycled aggregates. Three of the columns were exposed to standard ISO-834 fire for 30, 60 or 90 minutes, while the reference specimen was not exposed. Sixty days after fire exposure, the columns were tested under constant axial load and reversed cyclic lateral displacements simulating earthquakes. Test results are evaluated in terms of lateral load capacity, ductility, stiffness and energy dissipation. In addition, an analytical study was conducted to predict the lateral load-displacement response of fire-damaged columns built with recycled aggregates.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2022The inverter with reverse connected double converter driving unbalanced loads
Can, Erol
Inverter circuits play an important role in providing energy to multiple loads or energy lines. In cases where power lines or loads are unbalanced, it is important to balance and regulate the power it carries. Therefore, in this study, an inverter structure with an inverted connecting double dc-dc converter is used to drive unbalanced loads. While load balancing is performed by changing the widths of the pulse width modulation that make up the voltage in load balancing methods in other inverter studies, the maximum point of the generated voltage is changed by affecting the operating times of the converters in this study. First, the circuit structure and the working order of the circuit are given. Then three-phase balanced and unbalanced loads are driven. The unbalanced loads driven are finally balanced with the proposed circuit structure. Distortions of load currents are decreased as %3, 51. This distortion value is lower than 4% reported by the international IEEE, while the obtained load currents maintain a smooth sinusoidal structure.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2022A new multi-level inverter with reverse connected dual dc to dc converter at simulation
Can, Erol
It is very important to drive loads and control the electrical devices with changing electrical energy levels and change a voltage form. While DC-DC converters are used to change the value level of direct current (DC) electrical energy, inverters are used to change its form such as alternating voltage. Unlike these studies in the literature, for the first time, dc-dc converters are used to a new device structure to convert dc electrical energy into alternating current (AC) electrical energy and they can also change an amplitude of the multi-level voltage. So, the paper presents a multi-level inverter with reverse connected dual dc to dc converter. Firstly, the circuit structure and the signals that control the circuit are given and the operating logic is explained. Then, the proposed circuit is gradually modeling in MATLAB Simulink. After that, the circuit is operated in MATLAB Simulink and its performance is measured. According to the results obtained, the new circuit structure gives highly successful results.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2022Special Feature on social, economic, and spatial impacts of COVID-19 pandemic in Turkey
Baycan, Tüzin; Tuysuz, Suat
This Special Feature investigates the social, economic, and spatial impacts of the COVID-19 pandemic in Turkey and highlights the factors differentiating Turkey from the other countries. The articles contributing to this Special Feature are classified into three main parts. The first group of articles addresses spatial implications of the COVID-19 pandemic in Turkey with a specific focus on the place-based factors affecting the spread of the pandemic, the determinants of pandemic-induced changes in intracity mobility, and the use of social media to forecast commercial real estate figures during COVID-19. The second group of articles investigates the social and economic implications of the COVID-19 pandemic and diversely affected economic sectors in Turkey. These articles analyze the vulnerability and resilience of regions and diversely affected economic sectors with a specific focus on the housing market that displays an opposite trend to international tendencies regarding transaction volumes and private rental housing prices. The third group of articles considers the economic impact of the COVID-19 pandemic from an international perspective. These articles analyze the impact of the COVID-19 pandemic on international trade with a specific focus on exports and the fragility of the global trade structure and network in the framework of global value chains. Analyzing the impacts of COVID-19 from different perspectives, the articles in this Special Feature reveal the factors differentiating Turkey from the other countries and highlight the challenges.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2022Experimental Study to Predict Bond-Slip Behavior of Corroded Reinforced Concrete Columns
Yalciner, Hakan; Kumbasaroglu, Atila
To perform accurate seismic analyses of corroded reinforced concrete (RC) buildings, it is necessary to predict the bond-slip relationships to modify the moment-curvature relationships. In this study, empirical models were developed to predict the bond strength of corroded RC columns. Twenty-five RC columns were tested under combined cyclic lateral displacement excursions for three concrete strength levels-specifically, 9, 27, and 37 MPa (1305, 3915, and 5365 psi, respectively)-at two axial load ratios of 0.20 and 0.40 and at four corrosion levels. An accelerated corrosion method was applied to corrode the reinforcing bars embedded in the RC columns. The actual corrosion levels were determined by breaking the concrete and extracting all the longitudinal and transverse reinforcing bars from the RC columns. Three empirical models were developed. The first model was used to predict the development length of the corroded reinforcing bars. The second and third models were used to predict the bond strength and slip in the reinforcing bars as a function of the corrosion levels. The results indicated that previous models that predict the bond strength of corroded RC members were limited because of the theoretically considered development length of the noncorroded reinforcing bars.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2022EXERGY ANALYSIS AND DETERMINATION OF IRREVERSIBILTY OF A THERMAL POWER PLANT
Ata, İsmail; Tanürün, H. Erdi; Uzun, Sinem; Bayrak, Sebile; Acır, Adem
The exergy analysis and determination of irreversibility İ of a thermal power plant with 210 MW are presented in this study. The first- (ηI) and second-law (ηII) efficiencies, losses, and İ are computed for each component in the plant. The highest energy loss (43.538%) occurs with heat transfer to cooling water of the condenser, whereas the second loss (14.138%) occurs in the boiler. The highest İ value in the cycle (86.87%) occurs in the boiler followed by the turbine (5.95%). The ηI and ηII efficiencies of the whole plant are 38.64% and 31.68%, respectively. In addition, effects of the efficiencies in the temperature range from 5°C to 30°C are investigated. The ηI efficiency of the whole plant does not change, whereas the ηII efficiency decreases with increasing reference temperatures. In addition, the ηII efficiency is associated with environmental impact and sustainability.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2022The omnidirectional runway with infinite heading as a futuristic runway concept for future free route airspace operations
Aydoğan, Emre; Demirel, Soner
Purpose: The purpose of this paper is to create and analyze the effectiveness of a new runway system, which is totally created for the future free route operations. Design/methodology/approach: This paper researches and analyses the new generated runway concept with the fast time simulation method. Fuel consumption and environmental effect of the new runway system are calculated based on simulation results. Findings: According to different traffic density analyses the Omnidirectional Runway with Infinite Heading (ORIH) reduced fuel consumption and CO2 emissions up to 46.97%. Also the total emissions of the ORIH concept, for the hydro carbon (HC), carbon monoxide (CO) and nitrogen oxides (NOx) pollutants were lower than the total emissions with the conventional runway up to 83.13, 74.36 and 51.49%, respectively. Practical implications: Free route airspaces bring many advantages to air traffic management and airline operations. Direct routes become available from airport to airport thanks to free route airspace concept. However, conventional single runway structure does not allow aircraft operations for every direction. The landing and take-off operations of a conventional airport with a single runway must be executed with only two heading direction. This limitation brings a bottleneck direct approach and departure route usage as convenient with free route airspace concept. This paper suggests and analyzes the omnidirectional runway with infinite heading (ORIH) as a solution for free route airspace. Originality/value: This paper suggests a new and futuristic runway design and operation for the free route operations. This paper has its originality from the suggested and newly created runway system.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2022Economic impact of the COVID-19 outbreak in Turkey: analysis of vulnerability and resilience of regions and diversely affected economic sectors
Tuysuz, Suat; Baycan, Tüzin; Altuğ, Fatih
The COVID-19 outbreak has deeply affected the global economy of most countries and Turkey is no exception. However, the impacts of the outbreak differ on a regional basis, and both scientists and policymakers have neglected this regional differentiation. In an attempt to redress this situation, our study aimed to reveal the regional disparities related to the economic impacts of the outbreak and the dynamics that created this differentiation in Turkey. Our statistical analyses were carried out based on two different periods. The first period covered the first trimester when the outbreak began, and several shutdowns were implemented. The second period covered the second trimester when society began to open up again. The first trimester was termed the shock period, and the second trimester the recovery period. We developed a resilient–vulnerability index based on selected variables such as employment, energy consumption, exports, and the number of companies established and closed using a location quotient (LQ) analysis. While our index offers a picture of resilient and vulnerable regions, we also used this index as a dependent variable in our study. In the second stage, we focused on what kinds of dynamics gave rise to the resilience or vulnerability of a region. Our findings revealed that regions are economically affected by the outbreak at different levels. The regression analysis results showed that the innovation capacity and export levels of the regions predict regional resilience negatively, while firm size predicts positively. The recovery of regions also differed regionally. Our analyses show that Turkish regions with relatively larger economies recover more slowly, while regions with smaller economies recover more quickly.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2022Machine Learning-Based Estimation of Output Current Ripple in PFC-IBC Used in Battery Charger of Electrical Vehicles: A Comparison of LR, RF and ANN Techniques
Aslay, Fulya; Ting, Naim Suleyman
In this study, an artificial neural network (ANN) model is developed for the purpose of estimating the output current ripple of a power factor correction (PFC) AC/DC interleaved boost converter (IBC) used in battery charger of electrical vehicles (EVs) based on the inductance current ripple, switching frequency and load changes. Besides, the improved ANN model is compared with some different machine learning (ML) techniques like linear regression (LR), random forest (RF). The PFC-IBC is simulated with the PSIM simulation program to estimate the output current ripple. As a result, 336 output current ripple values are obtained based on inductance current ripple, different switching frequency and load changes. Then, the value of output current ripple is estimated by training the input parameters with LR, RF and ANN machine learning techniques (MLTs) for controlling the current harmonics drawn from the grid and for reliable charging of batteries. It is seen that the estimation value obtained with MLTs is quite compatible with the actual value obtained with the simulation. In addition, in the study carried out with the simulation, it takes a period of several days to obtain the estimation results; whereas, the operation of estimation with MLTs can be completed in a short period such as a few minutes. This clearly reveals the advantage of the MLTs. Therefore, this value is estimated through the MLTs with a high accuracy before the design of the charging device in order to maintain at a secure level the output current ripple posing considerable importance in electrical vehicle battery charge. Also, in this estimation process, LR, RF and developed ANN techniques are examined and compared separately in the WEKA program and it is observed that the developed ANN model proposes better results than other techniques.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2022Multi-objective optimization of a mini channeled cold plate for using thermal management of a Li-Ion battery
Kalkan, Orhan; Celen, Ali; Bakirci, Kadir
Mini channeled cold plates (MCCP) are an impressive choice for electric vehicles with a liquid-based thermal management system to keep the battery temperature within the desired range and to achieve a homogeneous temperature distribution. This paper came up with an optimum solution for maximum battery temperature (MBT), maximum temperature difference on the battery surface (MTD) and pressure drops in the channels (ΔP), which are vital parameters. Multi-objective optimization of geometric parameters and coolant flow rate of a designed MCCP which is experimentally investigated is carried out using the Desirability Function Approach. Firstly, the design of experiments (DoE) is generated using response surface method after determining the input variables and their levels. Then, each sample of DoE are modeled and analyzed numerically. Furthermore, the regression equations of the objective functions (MBT, MTD and ΔP) depending on the design parameters are developed and their variance analyzes are performed. Prediction accuracies of model equations developed for MBT, MTD and ΔP are 97.75%, 95.49% and 97.15%, respectively. As a result, optimum values of design variables, namely channel width (mm), distance between branches (mm), channel depth (mm), number of crossovers in branches and coolant flow rate (l/min) are 5, 5, 10, 13 and 0.7061, respectively.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2022A novel zero voltage transition boost converter and artificial neural network-based estimation of converter efficiency
Ting, Naim Suleyman; Aslay, Fulya; Sahin, Yakup
In this paper, a novel zero voltage transition (ZVT) boost converter is proposed, and the overall efficiency of the converter is predicted with an artificial neural network (ANN) model. In the proposed converter, the main switch is turned on by ZVT and turned off by zero voltage switching (ZVS). Also, the other semiconductor elements operate by soft switching (SS). Besides, the proposed snubber cell has the bidirectional direct power transfer feature. The theoretical analyzes of the converter are verified by an prototype having 50 VDC input voltage, 100 VDC output voltage, 250 W output power, and 100 kHz switching frequency. The overall efficiency of the converter in hard switching (HS) condition is increased from 87.2% to 95.4% thanks to proposed snubber cell. Moreover, the efficiency of converter at HS operation is estimated with ANN. For this estimation, 110 efficiency values are obtained based on the different switching frequency and the output power values. When the actual efficiency measurements and the estimation results obtained with the ANN model are compared, it is seen that the results overlap and is obtained very close result to the truth by ANN. Thus, owing to the ANN model, the semiconductor power elements will not need to be operated at high frequencies and overheating, and the damaging to the elements will be prevented. Finally, the efficiency curve measurement of the converter takes long time in the experimental study when it takes highly short time as a few minutes in the estimation with ANN.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2022Variable determined for optimization of alternating energy on the load by the adaptive Taguchi method
Can, Erol
It is important to find the optimum point in terms of energy quality in the studies for electrical energy conversions with the converter and inverter circuits. In such studies, the authors tried to find the optimum operating point by using control systems such as PID and Fuzzy Logic in closed-loop controls. When a large number of variables are involved in finding the optimum point, closed-loop control methods such as these may be insufficient to find the optimum point. Therefore, in this study, the Adaptive Taguchi Method (ATM) with the maximum-minimum value is used for the estimation of variables providing the optimum point for energy quality by using it in a multilevel inverter with a double DC-DC converter. While in traditional Taguchi Methods, dependent variables predict the results by revealing their effects on independent variables, in ATM, besides the effects of the independent variables, the effects of different dependent variables on each other are also estimated. First, the system to which the ATM will be applied is introduced. Then, the principles of applying the ATM are explained. In the known Taguchi method, variable values to be found with 34 = 81 trials, variables are estimated with 27 trials, while the values of two different dependent variables in the system can be found with 54 trials instead of 2×34= 2×81 trials. The resulting values to be estimated with the proposed ATM method are estimated with 27 trials instead of 2×81 or 54 trials. Finally, the observation results to be used for estimation are analyzed and evaluated. By trying the prediction results, it is seen that the proposed system is quite effective because the estimated result value that is %3.71 in the experiments gives a lesser distortion value than the values used for prediction.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2022Exploring factors affecting airport selection during the COVID-19 pandemic from air cargo carriers’ perspective through the triangular fuzzy Dombi-Bonferroni BWM methodology
Tanrıverdi, Gökhan; Ecer, Fatih; Durak, Mehmet Şahin
The COVID-19 pandemic has created unexpected demand for air cargo in terms of rapid mobility of critical basic needs. Air cargo carriers aim to maximize their profits by taking advantage of the current demand and using their limited capacity in the right place. At this point, some of the qualifications of the airports in the places where demand plays a crucial role in this decision of the carriers. Thus, evaluating the factors considered in the airport selection for air cargo carriers during the COVID-19 period is curious. This study proposes a triangular fuzzy Dombi-Bonferroni best-worst method (BWM) framework with vast flexibility to establish the priority preferences of factors considered in selecting airports. The fuzzy BWM model becomes a superior decision support system by combining the Bonferroni mean operator's ability to consider interrelationships between attributes and the flexibility of the Dombi operator. In this sense, we highlight eighteen criteria based on five airport aspects: location, physical features, performance, costs, and reputation. Findings reveal that the foremost aspects are location and costs, whereas the most crucial factors are airport charges and handling charges. The study suggests that airports should follow a low-price policy for airport-related charges without compromising their sustainability to have a share of the increasing number of air cargo flights, especially during the COVID-19 period, when airline passenger flights are decreased. The study is crucial in deciding the strategy and policy of air cargo carriers and airports during the pandemic period.
RDL Kalıcı Kaydıİncele
