Browsing by Author "Aydin M.M."

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    Prediction of pedal cyclists and pedestrian fatalities from total monthly accidents and registered private car numbers
    (Warsaw University of Technology, 2015) Ghasemlou K.; Aydin M.M.; Yildirim M.S.
    Accident prevention is relatively a complex issue considering the effectiveness of the injury prevention technologies as well as more detailed assessment of the complex interactions between the road condition, vehicle and human factor. For many years, highway agencies and vehicle manufacturers showed great efforts to reduce the injuries resulting from the vehicle crashes. Many researchers used a broad range of methods to evaluate the impact of several factors on traffic accidents and injuries. Recent developments lead up to capable for determining the effects of these factors. According to World Health Organization (WHO), cyclists and pedestrians comprise respectively 1.6% and 16.3% in traffic crash fatalities in 2013. Also in Turkey crash fatalities for pedestrian and cyclists are respectively 20.6% and 3% according to Turkish Statistical Institute data in 2013. The relationship between cycling and pedestrian rates and injury rates over time is also unknown. This paper aims to predict the crash severity with the traffic injury data of the Konya City in Turkey by implementing the Artificial Neural Networks (ANN), Regression Trees (RT) and Multiple Linear Regression modelling (MLRM) method.
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    Estimation of Container Traffic at Seaports by Using Several Soft Computing Methods: A Case of Turkish Seaports
    (Hindawi Limited, 2017) Gökkuş Ü.; Yildirim M.S.; Aydin M.M.
    Container traffic forecasting is important for the operations and the design steps of a seaport facility. In this study, performances of the novel soft computing models were compared for the container traffic forecasting of principal Turkish seaports (Istanbul, Izmir, and Mersin seaports) with excessive container traffic. Four forecasting models were implemented based on Artificial Neural Network with Artificial Bee Colony and Levenberg-Marquardt Algorithms (ANN-ABC and ANN-LM), Multiple Nonlinear Regression with Genetic Algorithm (MNR-GA), and Least Square Support Vector Machine (LSSVM). Forecasts were carried out by using the past records of the gross domestic product, exports, and population of the Turkey as indicators of socioeconomic and demographic status. Performances of the forecasting models were evaluated with several performance metrics. Considering the testing period, the LSSVM, ANN-ABC, and ANN-LM models performed better than the MNR-GA model considering overall fitting and prediction performances of the extreme values in the testing data. The LSSVM model was found to be more reliable compared to the ANN models. Forecasting part of the study suggested that container traffic of the seaports will be increased up to 60%, 67%, and 95% at the 2023 for the Izmir, Mersin, and Istanbul seaports considering official growth scenarios of Turkey. © 2017 Ümit Gökkuş et al.
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    Multimethod simulation approach for capacity design of a truck parking area in city ports
    (Eduem - Editora da Universidade Estadual de Maringa, 2022) Yıldırım M.S.; Aydin M.M.; Gökkuş Ü.
    The port induced freight can cause traffic congestion problems in city ports if road freight transportation is used. The secondary congestion problem arises from the pooling of the trucks at the port gates because of the delays of the port operations. The absence of the truck parking areas inside the port causes additional truck trips between the port and auxiliary truck servicing areas around the port. For reducing the impacts of the associated problems of the port induced truck traffic, truck parking areas can be used as buffer zones between the port and city. The purpose of this study is to develop a Decision Support System (DSS) with using multimethod simulation and cost optimization model for the capacity design of a truck parking area for a city port. The preliminary design of the parking area is used to estimate the development cost and outputs of the simulation model is coupled for the capacity optimization for truck arrival scenarios. The methodology is implemented for a case study of the İzmir city port in Turkey. The results of the study indicated that significantly different parking area capacities are required for different truck dwell times for the time restricted and unrestricted truck arrivals. © 2022, Eduem - Editora da Universidade Estadual de Maringa. All rights reserved.