Yazarlar
- Akkurt, Nevzat(10)
- Gul, Muhammet(7)
- Işık, Erdem(7)
- Yucesan, Melih(6)
- Acar, Ramazan(5)
- Konurhan, Zekeriya(5)
- Bayrakdar, Cihan(4)
- Kahraman, Gökhan(4)
- Keserci, Ferhat(4)
- Tuğan, Volkan(4)
- Utku, Anıl(4)
- Çılğın, Zeynel(4)
- İnallı, Mustafa(4)
- Göçmen, Elifcan(3)
- Korkmaz, Meral(3)
- Utku, Anil(3)
- Akbas, Ergun(2)
- Aksağan, Zülfükar(2)
- Akyol, Sinem(2)
- Bjarnadottir, Brynhildur(2)
- Black, Andrew(2)
- Celik, Erkan(2)
- Demir, Yakup(2)
- Derse, Onur(2)
- Erdem, Necla Seval(2)
- Evans, Ian S.(2)
- Geçkil, Tacettin(2)
- Gunnarsdottir, Gunnhildur E.(2)
- Güçlü, Yavuz Selim(2)
- Hudaverdi, Burcu(2)
- Imak, Andaç(2)
- Kjartansson, Bjarki T.(2)
- Koycegiz, Cihangir(2)
- Oddsdottir, Edda S.(2)
- Oskarsson, Hlynur(2)
- Saplıoğlu, Kemal(2)
- Sarı, Sacit(2)
- Shao, Shuangquan(2)
- Sigurdsson, Bjarni D.(2)
- Susam, Selim Orhun(2)
Yayınlar
- MakaleAçık Erişim2024Hybrid ConvLSTM Model for Wind Speed Prediction: A Case Study for India's Highest Wind Speed Cities
Utku, Anıl; Akyol, Sinem
Wind speed prediction is very important for logistics, energy production and renewable energy sources, aviation and maritime, agriculture, disaster management, environmental monitoring, construction, life planning and economic activities. In this study, it was aimed to predict the wind speeds of Jaisalmer, Kochi, Mangalore, Puri and Rameswaram, which are among the cities with the highest wind speeds in India. ConvLSTM hybrid model was developed by taking advantage of the effective features of CNN and LSTM models for wind speed prediction. With ConvLSTM, it is aimed to better determine the dynamics of wind speed by processing spatial and temporal data simultaneously. ConvLSTM has been extensively tested using an approximately 15-year hourly dataset consisting of RF, SVM, ANFIS, CNN and LSTM and wind speed measurements at 10 meters and 100 meters’ altitudes. Experimental results show that ConvLSTM has R2 values above 0.9 for almost all of the city and wind speed parameters, and outperforms the compared models with the lowest error values in terms of RMSE and MAE error metrics.
AtıfOpenAlex1TR Dizin1
İncele - MakaleYalnız künye2024Hybrid CNN-LSTM Model for Accurate Long-Term and Short-Term Temperature Prediction: A Case Study for Bingöl and Tunceli
Utku, Anıl
Extreme and sudden weather events experienced with global warming and climate change reveal the importance of accurate air temperature prediction. For this reason, it can be used to optimize decision-making processes for a wide range of applications from health and agricultural planning to energy consumption strategies. Artificial intelligence methods are successfully applied in many application areas due to their flexibility and efficiency. Traditional weather forecasting models are inefficient in detecting sudden fluctuations and complex, irregular patterns in data. Artificial in-telligence methods overcome these limitations thanks to their ability to process big data and capture long-term temporal dependencies. In this study, the aim is to predict future temperature changes more accurately by capturing patterns in past data with the developed CNN-LSTM hybrid model. The developed hybrid model is compared in detail with RF, SVM, CNN, and LSTM. The compared models were tested using daily average temperature data between 1961-2024 and hourly temperature data between 2020-2024. Experiments have shown that CNN-LSTM outperforms the compared models with R2 value above 0.97 in all scenarios.
AtıfOpenAlex2TR Dizin1İncele - MakaleAçık Erişim2024İklim Değişikliğinin Etkileri: Türkiye'de Yağış, Sıcaklık Anomalisi ve Su Kaynakları Üzerine Etkilerinin İncelenmesi
Korkmaz, Meral
İklim değişikliği, günlük yaşamımızı ve su kaynklarımızı önemli ölçüde etkileyen küresel bir sorundur. İklim değişikliği ile su kaynakları arasındaki karmaşık ilişkiyi anlamak, etkili önleme ve adapte stratejileri geliştirmek açısından hayati önem taşımaktadır. Bu çalışma, iklim değişikliğinin su kaynakları üzerindeki etkilerini araştırmayı ve bu konunun önemini vurgulamayı amaçlamaktadır. Su, sınırlı bir kaynaktır ve erişilebilirliği ile kalitesi insan refahı, tarım, enerji üretimi ve ekosistem sağlığı üzerinde doğrudan etki etmektedir. Ancak, iklim değişikliği yağış, sıcaklık ve buharlaşma desenlerini ve dinamiklerini değiştirerek suyun erişilebilirliği ve dağılımında önemli değişikliklere yol açmaktadır. Küresel sıcaklıkların artması, buzulların erimesine yol açarak tatlı su kaynaklarını sürekli olarak azaltmaktadır. Su kıtlığı daha yaygın hale geldikçe, sınırlı kaynaklar için rekabet artmakta ve potansiyel olarak çatışmalara ve sosyal huzursuzluğa yol açmaktadır. Su kaynaklarının önemi ve iklim değişikliğinin erişilebilirliği ile kalitesi üzerindeki kesin etkisi göz önüne alındığında, bu karmaşık ilişkiyi derinlemesine anlamamız kaçınılmazdır. Bu çalışma, iklim değişikliğinin su kaynakları üzerindeki sosyo-ekonomik ve çevresel etkilerini değerlendirmeyi amaçlamaktadır. Sonuç olarak, iklim değişikliğinin su kaynakları üzerindeki etkisi abartılamaz. Bu çalışma, Türkiye'de iklim değişikliğinin neden olduğu değişen yağış desenleri ve artan sıcaklıkların yeraltı ve yüzey su kaynakları üzerindeki etkilerini incelemektedir. Araştırma sonuçlarına göre, kış yağışlarında azalma ve sıcaklık artışı, özellikle Akdeniz ve Güneydoğu bölgelerinde kuraklık koşullarını şiddetlendirmektedir. Özellikle Akdeniz bölgesindeki göllerin uzun dönem uydu görüntüleri incelendiğinde ciddi anlamda azalma görülmektedir. Bu değişimler, yeraltı ve yüzey su kaynaklarının azalmasına ve su kıtlığı riskinin artmasına yol açmaktadır.
AtıfOpenAlex11TR Dizin3İncele - MakaleAçık Erişim2024Hindistan'daki Turistik Şehirlerin İklim Değişkenlerinin Tahminine Yönelik Hibrit ConvGRU Modeli
Utku, Anıl
Hava durumu tahmini tarım, sağlık, ulaşım, turizm, hava kalitesi ve endüstriyel üretim gibi alanlarda etkinliğin ve verimliliğin sağlanabilmesi açısından oldukça önemlidir. Geleneksel hava durumu tahmin modelleri uzun vadeli tahminlerde yetersiz kalmaktadır. Yapay zekâ yöntemleri, sıcaklık, nem, rüzgâr hızı ve hava basıncını gibi hava durumu verileri arasındaki karmaşık ilişkileri öğrenerek geleceğe dönük başarılı tahminler üretebilmektedir. Bu çalışmada, Hindistan'ın önemli turizm şehirlerinden olan Agra, Jaipur, Jodhpur, New Delhi ve Rishikesh'in sıcaklık, nem ve çiğ noktası gibi uzun vadeli iklim değişkenlerinin tahmin edilmesi amaçlanmıştır. Bu amaçla, geliştirilen ConvGRU hibrit modeli, RF, SVM, CNN, LSTM ve GRU modelleriyle kapsamlı bir şekilde karşılaştırılmıştır. 2010-2024 yılları arasına ait gerçek zamanlı ve güncel bir veriseti kullanılmıştır. Deneysel sonuçlar, ConvGRU’nun tüm şehirler ve iklim değişkenleri için 0,9’un üzerinde R2 değeriyle karşılaştırılan modellerden daha başarılı olduğunu göstermiştir.
AtıfOpenAlex3TR Dizin3İncele - MakaleAçık Erişim2024Scopus SJRQ2Regional Climate Change and Drought Dynamics in Tunceli, Turkey: Insights from Drought Indices
Korkmaz, Meral; Kuriqi, Alban
Global warming and climate change are causing temperatures to rise, which is having a negative impact on water resources. Climate change is a worldwide problem that affects and will continue to affect the frequency and intensity of natural disasters in many regions of the world. Tunceli region in Turkey, which until 10 years ago was known as an environmentally friendly city with abundant water resources and frequent rainfall, is experiencing a decrease in precipitation during the snowy winter season. This situation has made the investigation of climate change impacts an important issue in the region. Therefore, effective climate change adaptation strategies need to be developed. To determine these strategies, in this study, we assessed long-term drought conditions using multiple drought indices such as Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI), Normal Precipitation Index (PNI), and Aridity Index (AI). The SPI and RDI analyses were performed in annual reference periods on a time scale of 3, 6, 9, and 12 months using temperature, precipitation, and evaporation data. Consequently, the SPI and RDI results were compared, and both indices show similar behavior in dry, wet, and normal seasons. Nevertheless, RDI shows less variation between different time scales, which is an advantage over SPI and is probably due to the inclusion of potential evapotranspiration in RDI. The variations in PNI between humid and dry sub-humid categorizations throughout the years, combined with the AI results, indicate that the Tunceli region predominantly experiences a climate ranging from dry sub-humid to semi-arid. This study could help decision-makers take effective measures to become more resilient to climate change in temperate climate regions and take important steps toward sustainable water resources management.
AtıfScopus17WoS15OpenAlex20
İncele - MakaleYalnız künye2024Scopus SJRQ2Stress–strength reliability for electricity systems based on the Bernstein copula approximation
Susam, Selim Orhun; Hudaverdi, Burcu
Electricity is a critical resource for modern society, and its availability is essential for various aspects of daily life, from powering homes to supporting industrial processes and infrastructure. Ensuring a reliable supply of electricity is vital for economic stability and the well-being of a population. As the world moves toward more sustainable and renewable energy sources, understanding the reliability of these sources compared to traditional fossil fuels is crucial. In this study, we develop a methodology that enables the measurement of stress–strength reliability when electricity consumption is considered as the strength variable, positioned between electricity generation from renewable energy sources and fossil fuels as stress variables. We achieve this using the copula-based reliability with Bernstein copula approximation. The methodology is applied to the U.S. monthly electricity data. The result shows that the current rates of electricity output from fossil fuels and renewables will not be sufficient to meet the demand for electricity.
AtıfScopus2WoS3OpenAlex3İncele - MakaleAçık Erişim2024Scopus SJRQ1Late pleistocene glacial history of Mount Karadağ, SW Türkiye
Bayrakdar, Cihan; Çılğın, Zeynel; Sarış, Faize; Yeşilyurt, Serdar; Keserci, Ferhat; Büyükdeniz, Yusuf; Halis, Onur; Vockenhuber, Christof; Ivy-Ochs, Susan; Akçar, Naki
Glacial landforms in the southwestern part of the Anatolian Peninsula are found at lower elevations than the rest, suggesting that glaciers were present during the Late Pleistocene. Karadağ, located west of the Western Taurus Mountains, provides evidence of the climatic conditions that facilitated this extensive glaciation. It is characterized by numerous peaks exceeding 2300 m above sea level (asl), with the highest peak reaching 2418 m, making it the region's largest glaciation area. This high mountain mass is composed mainly of limestone and dolomite. This study focuses on the glacial landforms in Karadağ to reconstruct the Late Pleistocene glacial chronology and palaeoclimate of the Western Taurus Mountains. We employed detailed UAV photogrammetry, extensive fieldwork and mapping, surface exposure dating with cosmogenic 36Cl, meteorological measurements, palaeoglacier reconstruction, and palaeo-equilibrium line altitude (pELA) calculations. Karadağ, a topographic barrier to humid air masses from the Mediterranean Sea, ranks as the second wettest area in the Western Taurus Mountains. At a meteorological station we installed in Karadağ, an annual precipitation of 1700 mm or more was recorded, highlighting its significant precipitation. In Karadağ, we have identified two glacial valleys with a maximum length of 4.5 km and six cirques. The glaciers reached their maximum extent around 22.4 ± 2.8 ka during the Last Glacial Maximum (LGM), facilitated by the lowering of the pELA to 2090 m. During the LGM, the glaciers covered an area of approximately 3.5 km2 and reached a maximum thickness of about 140 m. Sample TRKR 10 at 2015 m probably belongs to the LGM period. Although a single sample does not conclude definitive conclusions, the presence of the moraine at its highest position indicates the maximum thickness of the glacier. Following the LGM, two more significant glacier advances occurred during the Lateglacial (15.5 ± 2.7 ka) and the Younger Dryas (12.4 ± 1.1 ka). During the late Pleistocene glaciations, and especially during the LGM, Karadağ probably received more precipitation than today, leading to the formation of glaciers at relatively lower elevations than on the Anatolian Peninsula.
AtıfScopus4OpenAlex10İncele - Kitap BölümüAçık Erişim2024High Entropy Materials for CO2 Conversion
Simsek, Telem; Guler, Seval H.; Guler, Omer; Simsek, Tuncay
Metal-based oxides, ceramics, and composite catalysts are commonly used for CO2 conversion. To increase the efficiency of these catalysts, strategies such as heterostructure, defect engineering, nanolayers, mesoporous structure development, and oxygen vacancy engineering are used. In recent years, highly stable high entropy alloys (HEAs), which include at least five different elements in equimolar or nearly equimolar ratios, have recently come to be recognized as promising CO2 conversion catalysts. Their unique properties enable enhanced reactivity and selectivity, making them highly valuable in addressing CO2 emissions and climate change challenges. When several elements are included in a catalyst, surface microstructures with different atomic configurations and active catalytic sites are produced. As a result, different adsorption modes arise for reactants and intermediates. In addition, the mixing of metal elements in varying atomic ratios causes changes in the electronic structure of metals. The distinct catalytic characteristics of HEAs are a result of modifications to their electronic structure brought on by lattice stretching, distortion, and compositional alterations.
- MakaleAçık Erişim2024Scopus SJRQ1Morphometric characteristics of glacial cirques and former glaciers in the Geyik Mountains, Western Taurus, Türkiye
Çılğın, Zeynel; Evans, Ian S.; Keserci, Ferhat; Canpolat, Ergin; Bayrakdar, Cihan
Using the Glacier reconstruction (GlaRe) toolbox, reconstructions of former glaciers in the Geyik Mountains, part of the Taurus Mountain system in southern Türkiye, show that an area of 132.5 km2 was glaciated in the last major glaciation, which left clear terminal and hummocky moraines. Glaciers were 1.4 to 12 km long and those from 49 cirques merged to form a broad 75 km2 piedmont glacier in the Namaras Valley, up to 400 m thick. A thorough analysis of morphometry of the 98 Geyik cirques, using the revised Automated Cirque Metric Extraction version 2 (ACME2) toolbox, shows that they are relatively small, with limited widths: the median length/width ratio of 1.29 is unusually high. With size, length and width increase faster than depth, demonstrating strong static allometry. Maximum slope averages 59°, minimum 3.3° and axial 25°. A combination of low hypsometric integral, high axial profile closure and high axial height-length integral is proposed as a measure of cirque development. The main summits are on sharp ridges on cirque crests, showing that they have been lowered by glacial erosion (by cirque development). Glaciation was strongly asymmetric, with cirque vector mean aspect between northeast and north-northeast. This shows the dominance of solar radiation effects, with some modification from westerly winds. Glacier palaeo- Equilibrium Line Altitudes (pELAs) rise northeastwards and cirque floor minimum altitudes (CFAs) rise toward east-northeast, both showing the importance of moist air from the Mediterranean, 38–55 km to the southwest. pELA averages 2208 m above sea level (a.s.l.) (2277 m area-weighted); CFA averages 2234 m. CFA varies mainly with summit altitudes; where related palaeoglaciers are short CFA is somewhat below pELA, but for longer ones it is above. The most likely palaeoclimate to form these glaciers involves a precipitation increase of 53–72 % with a temperature fall of 8 °C compared with present-day. The cirques formed under similar or less severe conditions.
AtıfScopus7OpenAlex15İncele - BildiriYalnız künye2024An Analysis of Dependence Relationships Between Covid-19 Pandemic and Environmental Conditions Cases Study in Indonesia, England, and Türkiye
Handhayani, Teny; Caglar, Durdane Kocacoban; Wibowo, F.W.
This study explores the causal relationships between environmental conditions and Coronavirus disease 2019 (COVID-19) using Bayesian networks in three geographically distinct cities: Jakarta (Indonesia), London (England), and Istanbul (Türkiye). The datasets collected from these cities span from January 2020 to October 2022, encompassing a variety of environmental variables (Particulate Matter (PM2.5), temperature, humidity, precipitation, wind speed, and Ultraviolet (UV) index) and COVID-19 variables (new cases, deaths, and population density). By using the PC algorithm and Greedy Equivalence Search (GES) to generate causal graphs, and applying the Intersection-Validation (InterVal) method to derive agreement graphs, this research reveals significant geographical differences in how environmental factors influence COVID-19 dynamics. The Peter-Clark (PC) algorithm identifies conditional dependencies, while GES optimizes the structure of the causal graph. The study highlights the significant impact of temperature, UV index, and humidity on COVID-19 dynamics, emphasizing the importance of localized public health strategies tailored to specific environmental conditions. These findings contribute to the understanding of environmental influences on COVID-19 and offer valuable insights for future research and policy-making aimed at mitigating the impact of pandemics in diverse geographical settings.
AtıfScopus3OpenAlex2İncele - MakaleAçık Erişim2024Scopus SJRQ2A comparison of the performance of different innovative trend assessment approaches for air temperature and precipitation data: an application to Elazığ Province (Turkey)
Acar, Ramazan
In this study, the temporal variability of monthly total precipitation and monthly average temperature data of Palu station were analyzed. In addition to statistical analysis such as Mann–Kendall (MK) and SR, innovative polygon trend analysis (IPTA), innovative trend analysis (ITA), and combination of Wilcoxon test and scatter diagram (CWTSD) methods were used in the study. A total of 24 trend analyses (for 12 months of precipitation and temperature data) were conducted for each method used for temperature and precipitation parameters in the study. Look-ing at the results of these methods, a decreasing trend was detected only in December for precipitation data, common to all methods. For temperature data, an increasing trend was detected only in February and March. With the application of the IPTA, an increasing trend in some months and a decreasing trend in other months were detected for the two parameters. The Wilcoxon test exhibits significant consistency with the MK and Spearman's Rho (SR) in terms of the statistical trend, according to the examination of temperature and precipitation data using the CWTSD approach, which is relatively recent. Furthermore, the visual trend analysis demonstrates high consistency between the NO-ITA and Sȩn-ITA approaches.
AtıfScopus23WoS20OpenAlex34İncele - MakaleYalnız künye2024Scopus SJRQ2Urban heat island patterns in garden cities: Putrajaya as a case study
Harun, Zambri; Akkurt, Nevzat; Khor, Yu King; Abbas, Ashraf A; Lotfy, Eslam Reda
The garden-city model, characterised by sprawling urban expansion and extensive open spaces, features green and water surfaces alongside substantial road networks, large parking lots and unshaded lands. This diverse landscape contributes to uneven air temperature distribution within the city. Our study investigated urban heat island (UHI) patterns in various urban environments within Putrajaya, focusing on rural, business, residential and near-water areas. Atmospheric data were collected over a year. Putrajaya exhibits two distinct UHI patterns: cool-day-hot-night in residential zones and hot-noon-temperate-elsewhere in impermeable areas. Business areas display alternating patterns based on seasonal climatic conditions and anthropogenic factors. The efficacy of artificial water bodies as a UHI countermeasure in garden cities depends on the size of the water body and the nature of the surrounding land cover. Shaded and green areas exhibit UHI intensities limited to 3°C, while impermeable areas, regardless of proximity to water surfaces, experience UHI up to 6°C. Overall, the garden-city model tends to restrict UHI variations within −1 to 3°C compared to −2 to 4°C in nearby Kuala Lumpur.
AtıfScopus9OpenAlex7İncele - MakaleAçık Erişim2023An Optimization Approach for A Biogas Supply Chain using Goal Programming and Mixed Integer Linear Programming
Derse, Onur; Göçmen, Elifcan
Environmental concerns prompt the world for a transition to renewable energy sources from fossil energy. Reducing the dependency on non-renewable sources of energy is prerequisite for the sustainable world and less environmental pollution. Biogas energy, which is one of the most important renewable energy sources, is produced by burning organic wastes and can be used in many different fields. In this study, a two-stage approach is undertaken to optimize a biogas supply chain design by incorporating of 30 districts in Izmir. In the first stage, the selection of the most suitable biogas plants is considered by the goal programming approach, which is of great importance to decide the optimal location with high energy potential. The most suitable sites for the biogas plants are obtained as Konak and Narlıdere districts. In the second stage, the location problem of the biogas vehicle charging stations (BVS) for biogas vehicles is handled considering the results of the first stage using mixed integer linear programming (MILP) approach. Computational results demonstrate that it would be more appropriate to establish BVS in 12 districts of İzmir. The model and solution approach are pioneering for supply chain problems and an efficient tool for renewable energy plans.
AtıfOpenAlex3İncele - MakaleAçık Erişim2023Rüzgâr Enerji Santrali (RES) Yer Seçimi için BWM-CBS Tabanlı Bir Yaklaşım: Tunceli Örneği
Konurhan, Zekeriya; Başaran, Erkin
Günümüz dünyasında fosil yakıtların yerine alternatif bir enerji kaynak arayışı oldukça popüler bir yaklaşımdır. Güneş panelleri ve rüzgâr enerjisi santralleri gibi yenilenebilir enerji kaynakları fosil yakıtların alternatifleri arasındadır. Rüzgâr enerjisi santralleri hem denizde hem de karada olmak üzere dünyanın birçok bölgesinde aktif olarak kullanılmaktadır. Türkiye’de de RES’ler özellikle 2000’lerin başından itibaren kullanılmaya başlamıştır. Türkiye’deki RES’ler daha çok Ege ve Marmara Bölgesinde yer almaktadır. Çalışma alanı olan Tunceli’de ise herhangi bir RES bulunmamaktadır. Bu çalışmanın temel amacı Tunceli için uygun RES alanlarını önermektir. Bu kapsamda Best-Worst yöntemi (BWM) CBS’ye entegre edilerek kullanılmıştır. BWM yöntemi ikili karşılaştırmaya dayanan Çok Kriterli Karar Verme (ÇKKV) yöntemidir. Çalışmada BWM modeli kullanılarak “topografya”, “sosyo-ekonomik”, “teknik” ve “lokasyon” olmak üzere dört ana kriter altında 16 kriter belirlenmiştir. Her bir kriter farklı disiplinlerden uzmanlar tarafından anket olarak değerlendirilmiş ve uygun yer seçimi için kullanılmıştır. 16 kriter için ayrı ayrı haritalar oluşturulmuş, kriterlerin açıklamaları yapılmış ve bu haritalar sonuç haritasında kullanılmıştır. BWM modeli kullanılarak tespit edilen kriter ağırlıkları CBS’ye entegre edilerek Tunceli için uygun RES kurulum alanları belirlenmiştir. Buna göre, Tunceli’nin güneydoğusunda yer alan Pertek ve Mazgirt çevresi ile Pülümür’ün kuzeyi ve Çemişgezek’in çevresinde fiziki coğrafya açısından uygun şartları sağlayan bazı alanlar RES kurulumuna elverişlidir.
AtıfOpenAlex5TR Dizin3İncele - MakaleAçık Erişim2023An integrated Bayesian Best-Worst Method and GIS-based approach for offshore wind power plant site selection: A case study in North Aegean and Marmara Sea (Türkiye)
Gul, Muhammet; Yucesan, Melih; Konurhan, Zekeriya
In today’s world, renewable energy sources are in great demand due to the negative ef- fects of fossil fuels on the environment. Wind power plants are an important renewable energy source alternative to fossil fuel consumption. Offshore wind farms established in coastal areas and seas are used effectively in many parts of the world. The wind power plants, especially in the Northwest region of Turkey and the Aegean coasts, constitute an important potential. This study selects suitable sites for offshore wind farms in the Marmara Sea and North Aegean Coasts of Turkey by integrating the Bayesian Best-Worst method (BWM) and GIS. Bayesian BWM improves the traditional BWM integrating the preferences of multiple experts. In the study, 17 sub-criteria were determined under four main criteria of “technical”, “socio-economic”, “environment,” and “location”. Ex- perts’ judgments through the filled enabled the criterion weights to be obtained. The criteria weights found using the Bayesian-BWM model were integrated into the GIS, and suitable locations for the offshore wind farm were determined. Accordingly, the study area off the coasts of Aliağa, Bozcaada, and Gökçeada on the North Aegean coast, and the part south of the Marmara Sea and the area around Kapıdağ Peninsula are sugges- ted as suitable areas for wind power plants.
AtıfOpenAlex7İncele - Kitap BölümüYalnız künye2023A GIS-Based BWM Approach for the Location Selection of Solar Power Plant in Tunceli Province (Turkey)
Konurhan, Zekeriya; Yucesan, Melih; Gul, Muhammet; Rezaei, J; Brunelli, M; Mohammadi, M
The world has recently tended to turn to renewable energy sources due to the serious negative impact of fossil fuels on the environment. One of the top priorities for solar energy is the selection of the most suitable location of the solar power plant to be established. In this study, the most suitable solar power plant location selection for Tunceli, a province located in the eastern part of Turkey, is studied with an approach based on Geographic Information System (GIS) and the best-worst method (BWM). A weighting was performed using the BWM model for 16 sub-criteria under four the main criteria of “climatic conditions, geographical conditions, land conditions, and location (distance to crucial points)”. Afterward, maps were created for these criteria, and a 6-point scale in the legends of each map for each sub-criteria was applied. Finally, the most suitable locations were determined with GIS-based calculations.
AtıfScopus6WoS5OpenAlex7İncele - MakaleYalnız künye2023Scopus SJRQ1Modeling the form, distribution and paleoclimatic implications of former glaciers in the Teke Peninsula (Eastern Mediterranean, Turkey)
Keserci, Ferhat; Bayrakdar, Cihan; Çılğın, Zeynel; Evans, Ian S.
The Western Taurus Mountains on the Teke Peninsula, Southwestern Turkey, saw substantial glaciation in the late Quaternary period. Accurate reconstructions of former glacier extent in this relatively marginal area of glaciation are important for establishing the paleoclimate in the Eastern Mediterranean Basin. From west to east, the mountains of Sandıras, Karadağ, Akdağ (Kaş), and Beydağları preserve clear evidence of cirques and moraines, representing glacial valley land systems. This study used calculation tools for Glacier Reconstruction, (GlaRe) and Equilibrium Line Altitude (ELA), with glacier outlines based on the geomorphological evidence and Digital Elevation Models (DEMs), to determine the distribution and ELAs of former glaciers and to estimate paleotemperature and paleo-precipitation during the maximum ice extent. The results are analyzed at three scales: for each glacier, between glaciers and between mountain ranges. While the glaciation was at its peak, we estimate that glaciers covered a total area of 26.4 km2 (1.28 ± 0.08 km2 on Sandıras Mountain, 3.86 ± 0.23 km2 on Karadağ, 16.17 ± 0.970 km2 on Akdağ (Kaş), and 5.09 ± 0.30 km2 in Beydağları): the longest glacier was in Akdağ (Kaş) with a length of 5787 m. Average paleo-ELA (pELA) was calculated as 2077 m a.s.l in Sandıras, 2097 m a.s.l in Karadağ, 2565 m a.s.l in Akdağ (Kaş), and 2468 m a.s.l in Beydağları. Glacier modeling estimated that the maximum ice thickness in Akdağ was 240 m ± 14, and the average thickness 75 ± 4 m. Among these mountains, Karadağ had the lowest elevation to which glaciers descended (1760 ± 16 m a.s.l). Topographic analyses revealed that glaciers formed in the four mountains mostly in the North-facing localities with highest slope values of 18 to 30°. During the maximum glaciation period air temperature depression has been estimated as 8 to 9° Celsius; That required a precipitation increase of some 40 to 60 % compared to present, to produce the former glaciers mapped in the Teke Peninsula.
AtıfScopus10WoS9OpenAlex17İncele - MakaleYalnız künye2023Scopus SJRQ1A data-driven evaluating method on the defrosting effect of the air source heat pump system in Beijing
Guo, Yanhua; Shao, Shuangquan; Geng, Xudong; Li, Hao; Wang, Zhichao; Akkurt, Nevzat
The current demand-based defrosting initiation strategies of air source heat pumps (ASHPs) faces difficulty in achieving a balance between cost and robustness. Therefore, an efficient and innovative demand-based defrosting initiation strategy is proposed in this paper, based on the learned the degradation of heating capacity (DHC) method using data-driven model. Firstly, the DHC method is developed using the initially installed sensors without additional sensors to identify the frosty state. Subsequently, the fully connected neural network (FNN) model is established for predicting frosty state using field measured data from the ASHP system. Finally, the effectiveness of the defrosting initiation strategy is further validated through practical testing. The results demonstrate that the DHC method provides a reliable database for training the FNN model, resulting in an impressive accuracy of 91.43% for predicting the frosty state in the testing set. By adopting the innovative demand-based defrosting initiation strategies, the defrosting frequency, heating loss, and power consumption are respectively decreased by 66.3%, 2.1%, and 6.0% with the SCOP enhanced by 8.6% during a heating season. The promising results highlight that the proposed strategy effectively reduces costs while ensuring the efficiency of demand-based control.
AtıfScopus23WoS22OpenAlex27İncele - MakaleYalnız künye2023Scopus SJRQ2Numerical investigation of the effect of using louver baffles on thermal performance in solar air collectors
Tuğan, Volkan; Işık, Erdem
Conventional flat plate solar air collectors have advantages such as low cost and simple design. However, their thermal efficiency is lower than that of other designs. The thermal efficiency of these collectors can be increased by detailed examination of parameters such as the shape, size, arrangement and material of the air duct. In this study, it is aimed to improve the thermal efficiency of solar air collectors. The effect of louver baffles, which were not previously used in solar air collectors, on thermal efficiency was investigated numerically via computational fluid dynamics. Three different solar air collectors with flat plates, segmented baffles, and louver baffles were compared in terms of thermal efficiency. In addition, pressure drops in solar air collectors were investigated. The mass flow rate of the air in all collectors is assumed to be 0.04 kg/s. Analyzes were carried out between 09:00 and 16:00. The thermal efficiency values obtained during the day for solar air collectors with flat plate, segmented baffles and louver baffles are 27.66%–56.35%, 29.57%–58.82% and 30.09%–59.47%, respectively. The daily thermal efficiency values obtained for solar air collectors with flat plate, segmented baffles and louver baffles are 46.98%, 49.18% and 49.87%, respectively. The pressure drop for solar air collectors with flat plate, segmented baffles and louver baffles were found to be 4.62, 18.82 and 5.96 Pa, respectively. Based on the data obtained from this study, louver baffles are recommended for use in solar heating applications due to their high thermal efficiency and low pressure drop.
AtıfScopus5WoS5OpenAlex5İncele - MakaleYalnız künye2023Scopus SJRQ1An efficient hybrid weather prediction model based on deep learning
Utku, A.; Can, U.
Weather events directly affect human activities. In particular, extreme weather events with global warming, forest fires, and high air temperatures that cause drought make human life difficult. Effective and accurate weather prediction models are needed to take precautions against such climatic events. Therefore, it is essential to develop models that make precise weather predictions. Technological developments contributed significantly to developing successful deep learning-based weather prediction models. With a high success rate, this study proposed a hybrid weather prediction model based on Convolutional Neural Networks and Recurrent Neural Networks models. The proposed hybrid model was applied to the Jena dataset, which contains 14-parameter, large-scale meteorological data that were never utilized for weather prediction. The experimental results were compared with popular deep learning, machine learning, and statistical methods such as Auto-Regressive Integrated Moving Average, Convolution Neural Networks, Long-Short Term Memory, Multilayer Perceptron, Random Forest, Recurrent Neural Networks, and Support Vector Machine. As a result of these comparisons, the proposed hybrid model obtained the best prediction result for all metrics. For example, according to the weather prediction results for Jena, Germany, the proposed hybrid model got the results of Mean Squared Error: 0.035, Root-Mean-Squared Error: 0.189, Mean Absolute Error: 0.126, and R-Squared: 0.987.
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