Civil Engineering / İnşaat Mühendisliği

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Author: search.filters.author.Tayfur, Gökmen

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  • Article
    Citation - WoS: 18
    Citation - Scopus: 18
    In-Depth Exploration of Temperature Trends in Morocco: Combining Traditional Methods of Mann Kendall With Innovative Ita and Ipta Approaches
    (Springer Basel Ag, 2024) Qadem, Zohair; Tayfur, Gökmen
    This study examines trends in minimum and maximum temperatures at various climate stations located in different regions of Morocco for a period of five decades (1970 to 2019). Mann-Kendall, Sen's estimator, Innovative Trend Analysis (ITA) and Innovative Polygon Trend Analysis (IPTA) were used in the analysis. The results show significant fluctuations, at different time scales, between minimum and maximum temperatures at all stations. In coastal areas, such as Rabat Sale, minimum temperatures fell during January and February while other months saw increases. Average minimum temperatures in Rabat Sale tend to fall by 0.5 degree celsius. On the other hand, maximum temperatures in Rabat Sale rose by 0.2 degrees C. A decrease of 0.4 degree celsius for T-min and 1.6 degree celsius for T-max were observed in higher continental regions, such as Meknes. Other stations, such as Fez Sais (0.6 degree celsius T-min and 2.6 degree celsius T-max) and Taza (1.1 degree celsius T-min and 2.6 degree celsius T-max) showed an upward trend. Trends also vary, with notable increases in minimum and maximum temperatures, indicating different climatic dynamics according to altitude and locality. In particular, the ITA highlights a significant increase in annual maximum temperatures, with a P-value < 0.05 and trend slopes ranging from 0.0015 degree celsius per year in Rabat Sale to 0.0076 degree celsius per year in Taza. In addition, the IPTA results confirm diversity of upward and downward trends on monthly and seasonal scales, highlighting impact of geographical factors such as proximity to sea, topography, and continentality that contribute to formation of regional microclimates. The results highlight significant impact of climate change in Morocco.
  • Conference Object
    Citation - Scopus: 1
    Decoding and Predicting the Attributes of Urban Public Spaces With Soft Computing Models and Space Syntax Approaches
    (Education and research in Computer Aided Architectural Design in Europe, 2023) Yönder, Veli Mustafa; Doğan, Fehmi; Çavka, Hasan Burak; Tayfur, Gökmen; Dülgeroğlu, Özüm
    People spend a considerable amount of time in public spaces for a variety of reasons, albeit at various times of the day and during season. Therefore, it is of utmost importance for both urban designers and local authorities to try to gain an understanding of the architectural qualities of these spaces. Within the scope of this study, squares and green parks in Izmir, the third largest city in Turkey, were analyzed in terms of their dimensions, landscape characteristics, the quality of their semi-open spaces, their landmarks, accessibility, and overall aesthetic quality. Using linear predictor, general regression neural networks, multilayer feed-forward neural networks (2-3-4-5-6 nodes), and genetic algorithms, soft computing models were trained in accordance with the results of the conducted analyses. Meanwhile, using space syntax methodologies, a visibility graph analysis and axial map analysis were conducted. The training results (i.e., root mean square error, mean absolute error, bad prediction rates for testing and training phases, and standard deviation of absolute error) were obtained in a comparative table based on training times and root mean square error values. According to the benchmarking table, the network that most accurately predicts the aesthetic score is the 2-node MLFNN, whereas the 6-node MLFN network is the least successful network. © 2023, Education and research in Computer Aided Architectural Design in Europe. All rights reserved.
  • Article
    Citation - WoS: 3
    Citation - Scopus: 3
    Ensemble and Optimized Hybrid Algorithms Through Runge Kutta Optimizer for Sewer Sediment Transport Modeling Using a Data Pre-Processing Approach
    (Elsevier, 2023) Safari, Mir Jafar Sadegh; Gül, Enes; Dursun, Ömer Faruk; Tayfur, Gökmen
    Uncontrolled sediment deposition in drainage and sewer systems raises unexpected maintenance expenditures. To this end, implementation of an accurate model relying on effective parameters involved is a reliable benchmark. In this study, three machine learning techniques, namely extreme learning machine (ELM), multilayer perceptron neural network (MLPNN), and M5P model tree (M5PMT); and three optimization approaches of Runge Kutta (RUN), genetic algorithm (GA), and particle swarm optimization (PSO) are applied for modeling. The optimization and ensemble hybridization approaches are applied in the modeling procedure. For the case of hybrid optimized models, the ELM and MLPNN models are hybridized with RUN, GA, and PSO algorithms to develop six hybrid models of ELM-RUN, ELM-GA, ELM-PSO, MLPNN-RUN, MLPNN-GA, and MLPNN-PSO. Ensemble hybrid models are developed through coupling the ELM and MLPNN models with the M5PMT algorithm. The data pre-processing approach is applied to find the best randomness characteristic of the utilized data. Results illustrate that the RUN-based hybrid models outperform the GA- and PSO-based counterparts. Although the MLPNN-RUN and MLPNN-M5PMT hybrid models generate better results than their alternatives, MLPNN-M5PMT slightly outperforms MLPNN-RUN model with a coefficient of determination of 0.84 and a root mean square error of 0.88. The current study shows the superiority of the ensemble-based approach to the optimization techniques. Further investigation is needed by considering alternative optimization techniques to enhance sediment transport modeling. © 2023 International Research and Training Centre on Erosion and Sedimentation/the World Association for Sedimentation and Erosion Research
  • Article
    Citation - WoS: 7
    Citation - Scopus: 5
    Meteorological Drought and Trend Effects on Transboundary River Basins in Afghanistan
    (Springer, 2023) Hayat, Ehsanullah; Tayfur, Gökmen
    Afghanistan, as a landlocked country located within central and southwestern Asia, has an arid to semi-arid climate. Most of the people are involved in agricultural activities, and a major part of the country's gross domestic product depends on agriculture, but the country has the lowest water storage capacity. Consecutive periods of drought and rapid snowmelt due to climate change have made it more challenging for suitable water resource management practices. This study investigates the historical meteorological drought characteristics across the whole country by employing the Reconnaissance Drought Index for the period 1979-2019 using data from 55 meteorological stations. Trends in precipitation and temperature are also investigated using the Mann-Kendall's and the Sen's slope statistical tests. A four-decadal countrywide drought map is generated. Extreme and severe droughts were observed in 1999 and 2000 across the whole country. Moderate drought events have started to occur with a frequency of 3 to 5 years since 1999. The decadal annual rainfall values in each river basin indicate that rainfall has decreased in the last two decades with a significant decline in 1999-2008. The trends of increase in temperature and decrease in precipitation are indications of rapid climate change in the country, especially in the south, west, and southwest regions. Due to the intensity and frequency of the droughts, river flow rates have decreased; and therefore, there is a need for the upstream and downstream neighboring countries to come to terms with the phenomenon of a new normal in the hydrological cycle and accordingly revise new water sharing treaties.
  • Correction
  • Conference Object
    Citation - Scopus: 2
    Emerging Concept of Human Centric Lighting in Literature Review
    (IEEE, 2023) Kazanasmaz, Zehra Tuğçe; Köse, Fatma Büşra; Tayfur, Gökmen
    Human centric lighting is an umbrella concept which covers human health and well-being in general. As the conventional lighting techniques are based on horizontal workplane illuminance, it drives from the vertical eye level illuminance and its spectral distribution triggering the non-visual effects on humans. That is named as melanopic illuminance consequently. Its metrics have taken their place in lighting design literature and applications, with emergence of related standards subsequently. This literature overview contributes about the understanding the meaning human centric lighting due to transition from visual to non-visual effects of light, and how they direct recent research through light's impacts on human performance, emotions health and well-being, and relations to energy saving even. The shift from the concept of human centric lighting to circadian lighting design is obvious in very current studies. © 2023 IEEE.
  • Article
    Citation - WoS: 16
    Citation - Scopus: 19
    Meteorological Drought Assessment and Trend Analysis in Puntland Region of Somalia
    (MDPI, 2023) Muse, Nur Mohamed; Tayfur, Gökmen; Safari, Mir Jafar Sadegh
    Drought assessment and trend analysis of precipitation and temperature time series are essential in the planning and management of water resources. Long-term precipitation and temperature historical records (monthly for 41 years, from 1980 to 2020) are used to investigate annual drought characteristics and trend analysis in Somalia's northern region. Six drought indices of the normal Standardized Precipitation Index (normal-SPI), the log normal Standardized Precipitation Index (log-SPI), the Standardized Precipitation Index using the gamma distribution (Gamma-SPI), the Percent of Normal Index (PNI), the Discrepancy Precipitation Index (DPI), and the Deciles Index (DI) are used in this study for the annual drought assessment. The log-SPI, the gamma-SPI, the PNI, and the DPI could capture historical extreme and severe droughts that occurred in the early 1980s and over the last two decades. The results indicate that Somalia has gone through extended drought periods over the past quarter century, exacerbating the existing humanitarian situation. The normal-SPI, gamma-SPI, and PNI indicate less and moderate drought conditions, whereas log-SPI, DPI, and DI accurately capture historical extreme and severe drought periods; thus, these methods are recommended as annual drought assessment tools in the studied region. Not only are the PNI and DPI less correlated to each other, but their correlation coefficient (CC) with SPI-based drought indices are not as high as SPI-based indices which are close to unity. For the purpose of the trend analysis, the Mann Kendall (MK) test, the Spearman's rho (SR) test, and the Sen test are used. Furthermore, the Pettitt test is implemented to detect the change points and the Thiel-Sen approach is used to estimate the magnitude of trend in the precipitation and temperature time series. The results indicate that there is overall warming in the region which has experienced a significant shift in trend direction since 2000. The trend analysis of annual precipitation data time series shows that Bossaso and Garowe stations have significant positive trends, while the Qardho station has no trend. In 1997 and 1998, respectively, abrupt changes in annual precipitation are detected at Qardho and Garowe stations. Due to the civil war of more than three decades in Somalia and the non-institutionalized governance to inform historical drought conditions in the country, determining the most appropriate meteorological drought index would help to develop a drought monitoring system for states and the entire country.
  • Book Part
    Citation - Scopus: 4
    Application of Fuzzy Logic in Water Resources Engineering
    (Elsevier, 2022) Tayfur, Gökmen
    This chapter introduces the fundamentals of fuzzy logic (FL), fuzzy sets, and fuzzy model components such as the fuzzification, the fuzzy rule base, the fuzzy inference engine, and the defuzzification. The processes of the fuzzy model components are presented by working on the examples from the water resources engineering application problems. This chapter also discusses the merits and the shortcomings of the fuzzy modeling. Hydrological processes have inherent source of uncertainty, for which the fuzzy set theory can be an effective solution tool. © 2023 Elsevier Inc. All rights reserved.
  • Book Part
    Citation - Scopus: 1
    Developments in Sediment Transport Modeling in Alluvial Channels
    (Elsevier, 2022) Tayfur, Gökmen
    This chapter discusses the developments in the mathematical modeling of sediment transport dynamics in alluvial channels. Starting with early experimental and empirical studies, it goes on to treating the processes in 1D, 2D, and 3D uniform sediment transport. Finally, it describes the treatment of the processes in 3D nonuniform sediment transport considering turbulence effects. While introducing the advancements in mathematical modeling of the dynamics, the chapter also discusses the outstanding issues like the treatment of the particle fall velocity, the particle velocity, and sediment transport rate function. © 2023 Elsevier Inc. All rights reserved.
  • Book Part
    Citation - Scopus: 3
    Real-Time Flood Hydrograph Predictions Using Rating Curve and Soft Computing Methods (ga, Ann)
    (Elsevier, 2022) Tayfur, Gökmen
    This chapter introduces hydraulic and hydrologic flood routing methods in natural channels. It details hydrological flood routing methods of the Rating Curve and Muskingum. Based on the rating curve method (RCM), it presents real-time flood hydrograph predictions using the genetic algorithm (GA-based RCM) model. In addition, it presents how to make real-time flood hydrograph predictions using the artificial neural network (ANN). The chapter briefly introduces the basics of GA and details how to calibrate and validate the GA-based RCM model using measured real-time flood hydrographs. Similarly, after giving the basics of ANN, it shows how to train and test the ANN model using measured hydrographs. Real hydrograph simulations by the RCM, GA-based RCM, and ANN are presented, and merits of each model are discussed. © 2023 Elsevier Inc. All rights reserved.