Yazarlar
- Yön, Burak(15)
- Onat, Onur(11)
- Gul, Muhammet(10)
- Utku, Anıl(9)
- Celik, Erkan(8)
- Etli, Serkan(8)
- Dal, Murat(6)
- Güngör, Gizem Nur(6)
- Yucesan, Melih(5)
- Öncü, Mehmet Emin(5)
- Akgül, Melek(4)
- Ergen, Burhan(4)
- Kaya, Sema Kayapinar(4)
- Mete, Suleyman(4)
- Akkurt, Nevzat(3)
- Ceylan, Ebru Nalan(3)
- Derse, Onur(3)
- Doğan, Gürkan(3)
- Güneyisi, Esra Mete(3)
- Karataş, Lale(3)
- Konurhan, Zekeriya(3)
- Polat, Elifcan Göçmen(3)
- Tam, Gürkan(3)
- Özceylan, Eren(3)
- Akar, Tuba(2)
- Başaran, Erkin(2)
- Calayır, Yusuf(2)
- Dalkılıç, Neslihan(2)
- Erdem, Necla Seval(2)
- Erguven, Gokhan Onder(2)
- Gör, Mesut(2)
- Harun, Zambri(2)
- Isik, Sevket(2)
- Işık, Erdem(2)
- Kanat, Gurdal(2)
- Peyneau, Pierre-Emmanuel(2)
- Serin, Faruk(2)
- Uslu, Ali(2)
- Varolgüneş, Sadık(2)
- Yilmaz, Deniz(2)
Yayınlar
- MakaleAçık Erişim2023Deep Learning-Based Automatic Helmet Detection System in Construction Site Cameras
Korkmaz, Adem; Ağdaş, Mehmet Tevfik
Ensuring worker safety in high-risk environments such as construction sites is of paramount importance. Personal protective equipment, particularly helmets, plays a critical role in preventing severe head injuries. This study aims to develop an automated helmet detection system using the state-of-the-art YOLOv8 deep learning model to enhance safety monitoring in real-time. The dataset used for the study consists of 16,867 images, with various data augmentation and preprocessing techniques applied to improve the model's robustness. The YOLOv8 model achieved a 96.9% mAP50 score, outperforming other deep learning models in similar studies. The results demonstrate the effectiveness of the YOLOv8 model for accurate and efficient helmet detection in construction sites, paving the way for improved safety monitoring and enforcement in the construction industry.
AtıfOpenAlex15TR Dizin3
İncele - MakaleAçık Erişim2023Scopus SJRQ3Performance evaluation of steel-concrete composite structures designed in poorly graded soils
Etli, Serkan
In this study, the seismic behavior of steel concrete composite buildings in a specific region was investigated. For this purpose, 5-, 10-, 15- and 20-storey composite moment-resisting framed structures were designed. Moment-resist-ing composite framed structures are modeled with concrete-filled steel tube columns and designed and modeled using composite beams. The buildings are designed according to ÇYTHYE-2016 and TBEC-2018 regulations at design levels with high ductility. In the design of the designed structures, the peak ground acceleration value is 0.79 g, and the design ground is planned as ZE class. SeismoStruct software was used for the design and performance evaluation of the structures. During the performance evaluations of the structures, nonlinear static pushover and incremental dynamic analyzes were used. Uniform and triangular load distributions are adopted in the static pushover analysis and 16 earthquake ground mo-tions are used in the incremental dynamic analysis. Evaluation of the effect of the number of stories on the earthquake behavior of composite moment-resisting framed structures was investigated using the non-linear analyzes mentioned. Ac-cordingly, lateral response, overstrength factors, ductility, and dynamic behavior factor values for composite frame struc-tures were calculated and presented using the relevant analysis results. It has been calculated that the behavior factor of all moment-resisting composite framed structures can perform well above the design assumptions, whereas moment-resistant composite framed structures absorb seismic energy by using inelastic deformations. Ductility is almost 30% higher than the design assumption for international standards. As a result, it was concluded that these structures could continue to serve theoretically.
AtıfScopus6WoS3OpenAlex9
İncele - MakaleAçık Erişim2023Deterioration analysis of historical village house structure in Mersin Kanlıdivane archaeological area by UAV method
Karataş, Lale; Dal, Murat
The village house located in the Mersin Kanlıdivane archaeological site is one of the oldest settlements in the ruins, built in the second century. The house is mainly built of a yellowish beige limestone. This stone, which is the main material of the building, shows many deterioration patterns today. The aim of the study is to determine the dominant deterioration pattern of the stones in the village house structure in the Mersin Kanlıdivane archaeological site and to investigate the source of the deterioration. In order to investigate the deterioration patterns in the structure, the images obtained by UAV photogrammetry were interpreted and the types of deterioration were mapped. In the study, it is seen that even the types of material problems based on the smallest detail can be determined based on virtual visual inspection, thanks to UAV photogrammetry, without observing the structure in situ with UAV photogrammetry. The findings obtained in the study shows that the color change and surface loss deterioration on the stone surfaces has reached advanced levels as a result of the structure's exposure to the strong climate-induced sun and water effects for centuries. The results of the study show that the main damage observed on the stone surface of the structure is caused by the erosion by the effect of water. Restoration methods should be tried to stabilize the deterioration and replace the most degraded stones. It is recommended to use water-repellent surface coatings to protect the natural stone, especially against the intense water effect in the building.
AtıfScopus3OpenAlex3İncele - MakaleYalnız künye2023Scopus SJRQ2Effect of Using Eccentric Braces with Different Link Lengths on the Seismic Demand of CFST Column-Composite Beam Frames Subjected to Near-Field and Far-Field Earthquakes
Etli, Serkan; Güneyisi, Esra Mete
In recent years, in the light of technological developments, the utilization of composite members that enable the use of superior properties of concrete and steel together in earthquake-resistant building design has become widespread. In this study, 5-, 8-, 10-, 13- and 15-story composite moment-resisting framed buildings were designed using composite beams and concrete filled steel tube columns. The effect of using steel braces and the variation of the link length of the eccentric steel braces on the seismic demand of the composite buildings were investigated. For this, eight different cases with braces were considered and compared with the bare structure. The first case had concentric braces (having no link), and the other seven cases had eccentric steel braces with different link lengths classified as short, medium and long. The nonlinear dynamic response of braced and non-braced composite structures was evaluated under the effect of earthquake groups of far-field, near-field with and without pulse effects. Each earthquake group includes ten different ground motion records. SeismoStruct which is a fiber element-based software was used in modeling and analysis of the structures. Seismic behavior of the case studied structures was investigated comparatively through the demand parameters such as the maximum inter-story drift ratios, the maximum roof drift ratios and the deformation states in the structural elements. It was observed that the inclusion of the steel braces provided significant gains in dissipating seismic energy acting through composite buildings and the beam/column deformations decreased considerably, depending on the length of the link and the height of the structure. In some cases, significant damage was monitored in the link members; however, this type of deformation was limited.
AtıfScopus3WoS3OpenAlex18İncele - MakaleAçık Erişim2023Scopus SJRQ1Integrating stratified best–worst method and GIS for landslide susceptibility assessment: a case study in Erzurum province (Turkey)
Konurhan, Zekeriya; Yucesan, Melih; Gul, Muhammet
Landslides are among the most destructive geological disasters that seriously damage human life and infrastructures. Landslides mainly occur in mountainous regions around the world. One of the key processes to reduce these damages is to uncover landslide-exposed areas through different data-driven methods such as Geographical Information System (GIS) and multi-criteria decision-making (MCDM). In the literature, there are many studies developed with these fundamental tools. In this study, unlike the literature, a new landslide susceptibility assessment model is proposed by integrating GIS with the stratified best–worst method (S-BWM). This model has four main dimensions and 16 sub-dimensions under topography, environment-land, location, and hydrological factors, weighted with the S-BWM. A network was created considering the different states that may arise in the importance weights of these dimensions in the future. The transition probabilities of these states were predicted and injected into the classical BWM. Then, maps were created for these dimensions and classifications for each sub-dimension according to the map characteristics. Finally, the most susceptive landslide locations were determined with GIS-based calculations. To demonstrate the model’s applicability, a case study was conducted for the Erzurum region, one of Turkey’s landslide-prone regions. In addition, besides the landslide map, an analysis and discussion about the spatial distribution of susceptibility classes was presented, contributing to the study’s robustness. In the results of landslide susceptibility analysis, landslides are higher in the range of about 1600–2500 m. Approximately 42% (35.59 sq. km) of the study area has high landslide susceptibility, while 58% (64.41 sq. km) has medium and low landslide susceptibility.
AtıfScopus19WoS17OpenAlex18
İncele - MakaleYalnız künye2023Scopus SJRQ2New Deep Learning-Based Passenger Flow Prediction Model
Utku, Anıl; Kaya, Sema Kayapinar
The ability to predict passenger flow in transport networks is an important aspect of public transport management. It helps improve transport services, aids those responsible for management to obtain early warning signals of emergencies and unusual circumstances and, in general, makes cities smarter and safer. This paper develops a long short-term memory-based (LTSM-based) deep learning model to predict short-term transit passenger volume on transport routes in Istanbul. This prediction model has been created using a dataset that included the number of people who used different transit routes in Istanbul at one-hour intervals between January and December 2020. The proposed multilayer LSTM-based deep learning model has been compared with popular models such as random forest (RF), support vector machines, autoregressive integrated moving average, multilayer perceptron, and convolutional neural network. The experimental findings showed that the proposed multilayer LSTM-based deep learning model outperformed the other models with regard to prediction for each transfer route. Furthermore, RF, one of the machine learning models used, produced remarkably successful results.
AtıfScopus19WoS12OpenAlex16İncele - MakaleYalnız künye2023Scopus SJRQ1Sustainability performance analysis of micro-mobility solutions in urban transportation with a novel IVFNN-Delphi-LOPCOW-CoCoSo framework
Ecer, Fatih; Küçükönder, Hande; Kayapınar Kaya, Sema; Faruk Görçün, Ömer
Almost all megacities worldwide are under pressure from environmental pollution and excessive resource usage due to rapid urbanization and increasing urban population. Within this scope, micro-mobility solutions (MMSs), an extension to the primary urban transportation network, have become even more critical recently. However, when we executed a preliminary investigation concerning MMSs' sustainability, we noted some critical theoretical and managerial gaps: (1) the number of studies assessing MMSs using decision-making approaches is excessively scarce, (2) no paper in the literature deals with the MMSs' sustainability performance, and (3) there are no commonly accepted criteria set to assess the sustainability of the MMSs in the literature. The current study aims to present a practical and robust decision-making framework that can overcome excessively complicated uncertainties to evaluate the sustainability performance of MMSs. Further, it suggests a novel methodological framework, i.e., Delphi, Logarithmic Percentage Change-Driven Objective Weighting (LOPCOW), and Combined Compromise Solution (CoCoSo) methods with interval-valued fuzzy neutrosophic number (IVFNN) information, which can be defined as a reconciliation tool to set the criteria affecting the assessment processes. Findings present that computing time, scenic adoption, and accidents are the foremost criteria, whereas mini-electric VH, powered standing scooter, and powered seated scooter are the most promising MMSs, respectively. Findings reveal that computing time, scenic adoption, and accidents are the critical factors for the sustainability assessment of MMSs, whereas mini-electric VH, powered standing scooter, and powered seated scooter are the most promising MMSs, respectively. The current paper's overall outcomes and findings can assist practitioners and policy-makers in the urban transportation industry in setting sustainability policies and investing in the more rational and sustainable MMSs.
AtıfScopus104WoS91OpenAlex112İncele - MakaleAçık Erişim2022Rijit Bodrum Perdelerinin TBDY 2018 ile Tasarlanan Az Katlı Yapılardaki Etkisi Üzerine Bir İnceleme
Etli, Serkan
Çalışma kapsamında rijit bodrum perdelerinin 6 katlı betonarme bir binanın davranışına etkisi incelenmiştir. İncelenen yapının tasarımı, TBDY-2018'e uygun olarak 3 boyutlu olarak SeismoStruct yazılımında gerçekleştirilmiştir. Bunun için bina ilk etapta ZD sınıfı katta rijit bodrum perdeleri ile tasarlanmıştır. Daha sonra bu rijit bodrum perdeleri kaldırılarak ikinci bir yapı elde edilmiştir. Sonuç olarak bu iki yapının yatay yükler altındaki performansları incelenmiştir. Her iki durumda da yapılar 3 boyutlu olarak incelenirken doğrusal olmayan statik itme analizlerine tabi tutulmuştur. Modeller, iki farklı yatay yükleme koşuluyla doğrusal olmayan artımlı statik itme analizi ile her iki tasarım yönü için analiz edilmiştir. Sonuç olarak, rijit bodrum perde duvarlı ve perdesiz binanın performans faktörleri, aşırı güç faktörü, doğal aşırı güç faktörü, süneklik ve rijitlik faktörü değerleri açısından karşılaştırmalı olarak değerlendirilmiştir.
AtıfOpenAlex4TR Dizin4İncele - MakaleAçık Erişim2022Kentin simgesini görünür kılmak: kızkulesi’nden kızkalesi’ne bir aydınlatma diyaloğu
Akar, Tuba; Güngör, Gizem Nur
Kültür varlıklarının profesyonel aydınlatılması konusu başlı başına bir tasarım problemi iken kültür varlıklarının kentsel simge değeri olduğu durumlarda aydınlatma tasarımı çok daha ayrıcalıklı bir hal almaktadır. Tarihi kentlerde kentsel simgelerin aydınlatılması dünyada ve ülkemizde giderek yaygınlaşan bir uygulamadır. Bu uygulamaların profesyonel ve nitelikli tasarımlar olabilmesi için mimari, teknik, ekonomik ve ekolojik hassasiyetlere sahip olması gerekmektedir. Bu çalışmada, öncelikle tarihi kent simgelerinin aydınlatılması konusu kentsel ölçekte ve tekil ölçekte ele alınmış ve uluslararası örnekler üzerinden değerlendirilmiştir. Kentsel simge aydınlatması ile ilgili aktarılan bilgilerle bir teorik altyapı oluşturulmuş ve bu bilgiler ışığında İstanbul’ kentinin simgesi olan Kızkulesi ile Mersin kentinin simgesi olan Kızkalesi arasında simgesel değerleri baz alınarak bir aydınlatma diyaloğu kurulmuştur. Kızkalesi’nin mevcut aydınlatmasının tarihi yapının kültür varlığı değerleriyle bağdaşmaması, bu diyaloğun kurulma ihtiyacının temel sebebidir. Bu noktada Kızkulesi’nin profesyonel ve nitelikli aydınlatması bu aydınlatma diyaloğunun öncüsü olarak kabul edilmiştir. Bu bağlamda Kızkalesi’nin geçmiş aydınlatma süreçleri de göz önünde bulundurularak mevcut aydınlatması eleştirel bir bakış açısıyla ele alınmış ve Kızkalesi’nin de nitelikli bir aydınlatmaya sahip olması gerekliliği vurgulanmıştır.
AtıfOpenAlex1İncele - MakaleAçık Erişim2022Parametric Analysis of the Performance of Steel-Concrete Composite Structures Designed with TBDY 2018
Etli, Serkan
In this study, the seismic behavior of steel-concrete composite buildings designed using ÇYTHYE 2016 and TBDY 2018 was investigated. For this purpose, composite moment resisting frame buildings with concrete filled steel tube columns and composite beams with 5, 10, 15 and 20 stories are modeled. Buildings are designed at high ductility (DCH) levels. During the design of the DCH class structures, the design was carried out for the ZA soil class for 0.79 g PGA in the region selected from the earthquake map given in the regulations. Within the scope of the study, SeismoStruct software was used during the design and performance evaluation of the structures. Incremental dynamic analyzes were used along with nonlinear static pushover analyses. In the static pushover analysis, uniform and triangular load distributions of the lateral load are adopted. In the dynamic analysis, 16 earthquake ground motions were obtained from AFAD earthquake acceleration databases according to the relevant design area and used. The variation of the seismic behavior of CMRFs depending on the variation of the floor number was investigated using nonlinear analysis results. Accordingly, the variation in lateral response, overstrength factors and ductility factors for CMRF structures are presented comparatively. In addition, the section deformation capacities were investigated during the IDR changes during dynamic and static nonlinear analyses. The behavior factor of all CMRFs, especially the CMRFs studied in the case study, demonstrated above-expected performance according to the design assumptions.
AtıfOpenAlex18TR Dizin2İncele - MakaleAçık Erişim2022Trafik Kazalarının Makine Öğrenmesi Yöntemleriyle Analizi ve Tahmini: Kahramanmaraş İçin Örnek Bir Çalışma
Utku, Anıl; Yucesan, Melih; Bolat, Hüseyin
Dünyada her yıl 1 milyonun üzerinde ölümlü, 50 milyona yakın yaralanmalı trafik kazası meydana gelmektedir. Bu kazalarda ortalama her 2 saniyede bir trafik kazası yaşanırken her 50 saniyede bir ölümcül kaza ile sonuçlanmaktadır. Bu çalışmada, 2017 ile 2020 yılları arasında Kahramanmaraş il merkezi ve ilçelerinde gerçekleşen 28 adet öznitelikten oluşan 7929 adet trafik kazası makine öğrenme teknikleri ile analiz edilmiştir. Trafik kazalarının analizinde sınıflandırma, birliktelik kuralı ve görsel karşılaştırma yöntemleri kullanılmıştır. Sınıflandırma için NB, SVM, kNN, PART, AdaboostM1, J48 ve RF algoritmaları kullanılmıştır. Trafik kazalarının sınıflandırılmasında J48 algoritması en başarılı sonuçları elde etmiştir. Naive Bayes algoritmasının başarı düzeyi kötü olmasa da diğer algoritmalara oranla daha düşük kalmıştır. Tüm yöntemlerin ortak sonucu gelecekte yaşanabilecek ölümle ve yaralanmalı potansiyel kazaların daha çok sabah saat 04:00 ile 08:00 ve akşam saat 16:00 ile 20:00 arasında, Kahramanmaraş il merkezi ve Onikişubat ilçesinde yerleşim yeri içerisinde, Göksun ilçesindeki yerleşim yeri dışındaki eğimli ve virajlı yollarda ve Pazarcık ilçesindeki yerleşim yeri dışındaki bölünmüş yollarda yaşanma riskinin yüksek olduğu belirlenmiştir. Ayrıca meydana gelen kazalarda sürücülerin trafik ve hız kurallarına uymadığı, trafik lambası, trafik levhası, yaya yolu, emniyet şeridi ve banket gibi yol, çevre ve güvenlik ekipmanlarının yetersiz kaldığı belirlenmiştir.
AtıfOpenAlex2TR Dizin2İncele - MakaleAçık Erişim2022Scopus SJRQ1Medical waste management during coronavirus disease 2019 pandemic at the city level
Polat, E.G.
Coronavirus disease 2019 brings about the economic damage and loss of life. Thus, demand of personal protective equipment continues to increase, consequently an increase in infectious equipment pollution. Most of these wastes threaten the environment and increase the spread of diseases. This paper provides a research hypothesis whether effective medical waste management would prevent the possible impacts of coronavirus disease 2019-related waste issues on environment at the city level. To confirm this hypothesis, installation of waste treatment centre is addressed. Then, by incorporating uncertain waste generation amounts utilizing Jimenez method, a pickup routing is addressed to decide the pickup routes between the waste treatment centre and residential area. This study is first to assign the optimistic, realistic and pessimistic scenarios of the uncertain waste generation using time series analysis method and waste generation formulation. Also, L-type matrix is used to define, assess and prioritize the environmental and operational risks on waste generation formulation and to provide risk reaction strategies. Practicality of these approaches is illustrated in the case of Turkey. The computational results reveal the effectiveness of the integrated method, which ensures practical and theoretical insights controlling the waste generation to prevent virus propagation for health authorities.
AtıfScopus15WoS13OpenAlex19İncele - MakaleAçık Erişim2022Scopus SJRQ1How Covid-19 pandemic and partial lockdown decisions affect air quality of a city? The case of Istanbul, Turkey
Celik, Erkan; Gul, Muhammet
The world is currently struggling with a new type of coronavirus (2019-nCoV) pandemic that first appeared in Wuhan, China, and then spread to almost all countries. As in other countries of the world, public authorities in Turkey are implementing many preventive and mitigating partial lockdown (PL) actions against the virus's effects. Some decisions and policies implemented before and after March 11, 2020, when the first virus case has been identified, have reduced people and traffic circulation, which has also turned into some improvements in air quality. At this point, this study aims to investigate how this pandemic affects the air quality of a metropolis. A case study of the city of Istanbul, the most affected city with more than half of Turkey's cases, is performed. In our analysis, we observe, compare, and discuss the impact of the COVID-19 pandemic and PL decisions on Istanbul city's air quality. We consider the particulate matter (PM10), sulfur dioxide (SO2), carbon monoxide (CO), nitrogen dioxide (NO2), nitrogen oxide (NO), nitrogen oxides (NOx), and ozone (O3) concentrations. We used data from 19 air monitoring stations (AMSs) and obtained improvements in the air quality for the pandemic period. In summary, the concentration levels in PM10, NO2, NO, and NOx result in a clear decline in pandemic times compared to the normal times in Istanbul. On the other hand, a non-homogenous trend for SO2 and CO concentrations is observed for different AMSs. A partial increase in O2 concentration is obtained in the comparison of before and during the PL period.
AtıfScopus15WoS13OpenAlex22İncele - Kitap BölümüYalnız künye2022A Multi-attribute Decision-Making to Sustainable Construction Material Selection: A Bayesian BWM-SAW Hybrid Model
Alkan, Ramazan; Yucesan, Melih; Gul, Muhammet; Rezaei, J; Brunelli, M; Mohammadi, M
The increase in urbanization and developments in the production industry has led to rapid progress in the construction sector. Many new strategies are developed in the industry to reduce costs and improve building quality. In recent years, the necessity of sustainable construction practices comes to the fore to renew the building stock damaged as a result of natural disasters and reduce the cost concerns that arise in this situation to a reasonable level. Due to limited resources and environmental concerns, researchers and practitioners have begun to develop sustainable building materials. The problem of selecting these materials when constructing a new building is vital. In particular, depending on the sector's rapid growth in Turkey, it is becoming more and more important to select the best sustainable construction material. Therefore, this paper proposes a model to evaluate the most appropriate sustainable construction material via two multi-attribute decision-making (MADM) methods called “Bayesian Best-Worst Method (BWM) and Simple Additive Weighting (SAW)”. Initially, the criteria derived from existing literature were evaluated with the aid of construction sector-based respondents and extra information about the interrelationship between the criteria were determined by credal ranking in Bayesian BWM. Then, via SAW, the most appropriate material was selected among a set of alternatives. Two cases regarding sustainable insulating material selection are considered for the demonstration of the proposed MADM model.
AtıfScopus15WoS14OpenAlex13İncele - MakaleYalnız künye2022Scopus SJRQ2Effect of nonlinear modeling approaches used for composite elements on seismic behavior of composite framed buildings
Etlİ, Serkan; Güneyİsİ, Esra Mete
This study aims to assess the effect of nonlinear modeling approaches used for frame elements while appraising the seismic performance of the composite moment resisting frame (CMRF) buildings. To this, the accuracy and efficiency of two representative numerical models (namely, inelastic force-based frame element-distributed plasticity (DP) and inelastic force-based frame element-plastic hinge length (PHL) (lumped-plasticity)) for the columns and beams of CMRFs are evaluated comparatively. The number of stories of the buildings of the case study ranges from 5 to 15 and consists of columns made of concrete-filled steel tube sections and CMRFs designed with composite beams consisting of a combination of solid reinforced concrete slabs and steel beams. The structures are designed by considering high ductility level. Seismostruct software is used for design and performance analysis. During the performance evaluation of the structures, the nonlinear static pushover analysis is utilized as well as the incremental dynamic analysis. While performing the nonlinear static pushover analysis, the lateral loadings with uniform and triangular load distributions are used, and moreover, a series of earthquake ground motions are used in the incremental dynamic analysis. To evaluate the effect of the modeling approaches, the seismic response of the structures is assessed by comparing the load-displacement response, energy consumption, performance limit. Additionally, the behavior factor, dynamic behavior factor, inherent strength and overstrength factors, ductility factor and global yield value are discussed.
AtıfScopus2WoS2OpenAlex16İncele - MakaleAçık Erişim2022Scopus SJRQ1DEEP LEARNING BASED A COMPREHENSIVE ANALYSIS FOR WASTE PREDICTION
Utku, Anıl; Kaya, Sema Kayapinar
In its simplest definition, waste can be defined as any substance that is used, not needed and causes harm to the environment. Waste management covers control activities such as prevention of the formation of waste, reuse, separation according to its characteristics and type, storage, transportation, recycling and disposal. The main purpose of waste management is to leave a livable world to future generations, to create a sustainable environment, to protect natural resources, to save energy and costs, to reduce the rate of pollution and the amount of hazardous waste. In today's world where urbanization and industrialization rates are increasing, waste management is gaining importance. The aim of this study is to utilize waste data from Istanbul, Turkey's largest and fastest growing city, to estimate waste amount using a constructed Long Short-Term Memory (LSTM) based deep learning model. The developed LSTM-based model has been compared in practice with k-Nearest Neighbors (kNN), random forest (RF), Support Vector Machine (SVM), multi-layered perceptron (MLP) and Gated Recurrent Unit (GRU). As a result of the comparative and comprehensive analyzes, the experimental results showed that the developed LSTM-based deep learning method is more successful in the waste prediction problem than the other compared models.
AtıfScopus13OpenAlex13İncele - MakaleAçık Erişim2022Scopus SJRQ1MULTI-LAYER PERCEPTRON BASED TRANSFER PASSENGER FLOW PREDICTION IN ISTANBUL TRANSPORTATION SYSTEM
Utku, Anıl; Kaya, Sema Kayapınar
Predicting passenger movement in transportation networks is a critical aspect of public transportation systems. It allows for a greater understanding of traffic patterns, as well as efficient system evaluation and monitoring. It could also help with precise timing to emergencies or important events, as well as the improvement of urban transport system weaknesses and service quality. The number of transfer passengers demand in Istanbul, Turkey's biggest and most developed metropolis, was used to construct a real-world forecasting model in this study. The number of transfer passengers has been forecasted using popular machine learning methods such as kNN (k-Nearest Neighbours), LR (Linear Regression), RF (Random Forest), SVM (Support Vector Machine), XGBoost and MLP. The dataset utilized is made up of hourly passenger transfer counts gathered at two public transportation transfer stations in Istanbul in January 2020. Using MSE, RMSE, MAE and R2 parameters, each model's experimental data have been thoroughly evaluated. MLP has more successfully other machine learning algorithms in the majority of transportation lines, according to the experimental results.
AtıfScopus27OpenAlex25İncele - MakaleAçık Erişim2022Scopus SJRQ1Field reconnaissance and structural assessment of the October 30, 2020, Samos, Aegean Sea earthquake: an example of severe damage due to the basin effect
Onat, Onur; Yön, Burak; Öncü, Mehmet Emin; Varolgüneş, Sadık; Karaşin, Abdulhalim; Cemalgil, Selim
An earthquake with a magnitude ranging from Mw = 6.9 (KOERI) to Mw = 7.0 (USGS) struck Samos Island in the Aegean Sea on October 30, 2020, with an epicentre 70 kms from the İzmir city centre in Turkey. The earthquake took place at 14:51 local time (11:51 UTC). The peak ground acceleration (PGA) of this earthquake was recorded to be 0.179 g at the epicentre of the earthquake. This earthquake occurred at a depth of 17.26 km (AFAD (2020) İzmir Earthquake Report, (In Turkish)) and lasted 16 s. The main shock from the earthquake triggered a tsunami that hit the building stocks built near the coast. During the gradual deregulation of COVID-19 pandemic regulations, various events caused considerable damage to the building stock, particularly in the Izmir Seferihisar and Bayraklı regions and resulted in a massive disruption of daily habits. The main shock caused 117 deaths in both Turkey and Greece, and 1632 people were also injured in Turkey. Moreover, several injuries occurred in Greece. A total of 103 buildings collapsed, 700 were severely damaged, 814 buildings were moderately damaged, and 7889 were slightly damaged. The basic aim of this paper is to briefly present the past and present seismotectonic characteristics of the region, present building stock, and former structural conditions before the earthquake, assess structural performance and classify distinguished earthquake-induced failures and damage due to the basin effect.
AtıfScopus30WoS28OpenAlex29İncele - MakaleAçık Erişim2021Beton Dayanımının ve Kirişlerdeki Çekme Donatısı Oranının Orta Yükseklikli Betonarme Binaların Sismik Davranışı Üzerine Etkisinin Belirlenmesi için Artımsal Dinamik Analiz
Onat, Onur; Yön, Burak
Artımsal Dinamik Analiz (ADA), sismik yükler altında yapısal performansı değerlendirmek için birkaç farklı biçimde yaygın olarak kullanılan parametrik bir sonuç analizi yöntemidir. Bu yöntem, seçilmiş olan bir grup sismik kayıtın ölçeklenerek yapısal sisteme etki ettirilerek, bu etki altında, elastik tepkiden genel dinamik yapısal stabiliteye ulaşmayı öneren bir analiz türüdür. Bu çalışmada çekme donatısı oranı ve beton dayanımının orta yükseklikli betonarme yapıların sismik davranışı üzerine etkisi incelenmiştir. Sayısal çalışma olarak 5 açıklıklı, 5 ve 7 katlı iki farklı sayısal model oluşturulmuştur. Her bir model için üç farklı çekme donatısı oranı ve iki farklı beton sınıfı seçilmiştir. Çekme donatısı oranları, basınç bölgesindeki donatının yarısı, bir katı ve iki katı olarak belirlenmiştir. Sayısal modeller artımsal dinamik yük altında analiz edilmiştir. Bu analiz için on bir farklı sismik kayıt kullanılmıştır. Bu kayıtlar 0.2g’den 1.2g’ye kadar 0.2g artımlar ile ölçeklenmiştir. Yapılan artımsal dinamik analizler sonucunda yapısal sistemlerin taban kesme kuvvetleri ve karşılık gelen çatı katı deplasmanları karşılaştırılmıştır. Elde edilen analiz sonuçlarına göre kirişlerde çekme donatısı oranını arttırmak çatı katı deplasmanını düşürmese de katlar arası göreli ötelenmeyi azaltmıştır, böylelikle hasar seviyesini azaltacağı için hasar oranını düşürmektedir.
AtıfOpenAlex2TR Dizin1İncele - MakaleAçık Erişim2021A novel inter-story drift limit proposal for TBEC2018 and fragility prognosis with TSC2007
Onat, Onur; Yön, Burak
The basic purpose of this paper is to investigate and propose a novel inter-story drift limits for the currentTurkish Seismic Code to get easy structural assessment by using software. For this aim, numerical analysiswas performed by modeling two types of RC frame structures. One of them is 5 stories, the other of them is7 stories. Two different concrete classes, C20 and C25, were considered and three tension reinforcementratios were considered for analysis. Tension reinforcement ratios were determined by half of the compressivereinforcement, equal to compressive reinforcement and double the compressive reinforcement ratio.Incremental dynamic analyses (IDA) were performed on these buildings. In this study to execute IDA, elevenseismic acceleration benchmark records were multiplied with various scaling factors from 0.2 to 1.0.Maximum base shear and corresponding roof displacement responses obtained from IDA curves weregenerated according to these responses. IDA curves were compared with each other by deriving fragilitygraphs. According to results, proposed limits for the current Turkish seismic code (TBEC-2018) provide,0.6%, 2.4% and 3.3% respectively for MN, GV and GC, rather safe limits compared to drift limits presentedin the foredate seismic code (TSC-2007).
AtıfOpenAlex2TR Dizin2İncele
