Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 2Citation - Scopus: 2Soft Computing and Regression Modelling Approaches for Link-Capacity Functions(Czech Technical University in Prague, 2016) Koşun, Çağlar; Tayfur, Gökmen; Çelik, Hüseyin MuratLink-capacity functions are the relationships between the fundamental traffic variables like travel time and the flow rate. These relationships are important inputs to the capacity-restrained traffic assignment models. This study investigates the prediction of travel time as a function of several variables V/C (flow rate/capacity), retail activity, parking, number of bus stops and link type. For this purpose, the necessary data collected in Izmir, Turkey are employed by Artificial Neural Networks (ANNs) and Regression-based models of multiple linear regression (MLR) and multiple non-linear regression (MNLR). In ANNs modelling, 70% of the whole dataset is randomly selected for the training, whereas the rest is utilized in testing the model. Similarly, the same training dataset is employed in obtaining the optimal values of the coefficients of the regression-based models. Although all of the variables are used in the input vector of the models to predict the travel time, the most significant independent variables are found to be V/C and retail activity. By considering these two significant input variables, ANNs predicted the travel time with the correlation coefficient R = 0:87 while this value was almost 0.60 for the regression-based models.Article An Analysis of Vehicular Traffic Flow Using Langevin Equation(Faculty of Transport and Traffic Sciences, University of Zagreb, 2015) Koşun, Çağlar; Çelik, Hüseyin Murat; Özdemir, SerhanTraffic flow data are stochastic in nature, and an abundance of literature exists thereof. One way to express stochastic data is the Langevin equation. Langevin equation consists of two parts. The first part is known as the deterministic drift term, the other as the stochastic diffusion term. Langevin equation does not only help derive the deterministic and random terms of the selected portion of the city of Istanbul traffic empirically, but also sheds light on the underlying dynamics of the flow. Drift diagrams have shown that slow lane tends to get congested faster when vehicle speeds attain a value of 25 km/h, and it is 20 km/h for the fast lane. Three or four distinct regimes may be discriminated again from the drift diagrams; congested, intermediate, and free-flow regimes. At places, even the intermediate regime may be divided in two, often with readiness to congestion. This has revealed the fact that for the selected portion of the highway, there are two main states of flow, namely, congestion and free-flow, with an intermediate state where the noise-driven traffic flow forces the flow into either of the distinct regimes. © 2015, Faculty of Transport and Traffic Engineering. All rights reserved.Article Citation - WoS: 9Citation - Scopus: 10Modelling Trip Distribution With Fuzzy and Genetic Fuzzy Systems(Taylor and Francis Ltd., 2013) Kompil, Mert; Çelik, Hüseyin MuratThis paper explores the potential capabilities of fuzzy and genetic fuzzy system approaches in urban trip distribution modelling with some new features. First, a simple fuzzy rule-based system (FRBS) and a novel genetic fuzzy rule-based system [GFRBS: a fuzzy system improved by a knowledge base learning process with genetic algorithms (GAs)] are designed to model intra-city passenger flows for Istanbul. Subsequently, their accuracy, applicability and generalizability characteristics are evaluated against the well-known gravity- and neural network (NN)-based trip distribution models. The overall results show that: traditional doubly constrained gravity models are still simple and efficient; NNs may not show expected performance when they are forced to satisfy trip constraints; simply-designed FRBSs, learning from observations and expertise, are both efficient and interpretable even if the data are large and noisy; and use of GAs in fuzzy rule-based learning considerably increases modelling performance, although it brings additional computation cost.Article Citation - WoS: 7Citation - Scopus: 7Impacts of Planners' Different Viewpoints on Optimum Land-Use Allocation(Routledge, 2013) Türk, Ersin; Çelik, Hüseyin MuratDevelopment of different viewpoints/perspectives in the planning process and discussion of their empirical results will allow creation of "better land-use plans". In this sense, one of the deficiencies met by the land-use planners is lack of decision support system that can analyse the empirical results of different viewpoints analytically. The aim of this study is to analyse impacts between planners' different viewpoints and the optimum land-uses allocation empirically and analytically. The study uses a generalized land assignment model formulated by Hanink and Cromley (1998) [Land-use allocation in the absence of complete market values, Journal of Regional Science, 38(3), pp. 465-480] that integrates the geographical information systems with multi-criteria decision-making techniques in Cesme/Izmir in Turkey. The study results indicated that the model is very useful to analyse impacts between planners' viewpoint and optimum land-use allocation.Article Citation - WoS: 6Citation - Scopus: 7Determination of Optimum Environmental Conservation: Using Multi-Criteria Decision-Making Techniques(Taylor and Francis Ltd., 2011) Çelik, Hüseyin Murat; Türk, ErsinThe type and degree of conservation areas in Turkey legally dictate the kind of land uses that can and cannot take place in a conservation area. Thus, the conservation scheme is one of the most important criteria in designing an urban land-use plan. The aim of this study is to analyse the effects of various conservation decisions on land-use allocation holding everything else constant. This study uses a land-allocation mathematical programme formulated by Hanink and Cromley [(1998) Land-use allocation in the absence of complete market values, Journal of Regional Science, 38, pp. 465-480] that integrates the geographical information systems with a generalized assignment problem to determine an optimum level of conservation scheme in Cesme/Izmir, a coastal resort in Turkey. The findings state that the proposed technique is indeed very useful and promising to answer diversified practical issues on a more rational basis.Article Citation - WoS: 25Citation - Scopus: 34Sample Size Needed for Calibrating Trip Distribution and Behavior of the Gravity Model(Elsevier Ltd., 2010) Çelik, Hüseyin MuratConventional calibration algorithms of trip distribution models assume that the analyst has a whole base year trip matrix. To attain a whole trip matrix, the sample size for travel surveys needed to be as large as possible. However, this could be very expensive especially in large cities. Some studies in the past showed a small sized sample would be enough to estimate functional parameters of observed trip length frequency distribution. But the performance of a gravity model with small sized samples has never been addressed. This empirical study has shown that sample sizes as small as 1000 (even smaller for quick response studies) could be as dependable as large sample surveys using a line search calibration algorithm. © 2009 Elsevier Ltd. All rights reserved.Article Citation - WoS: 22Citation - Scopus: 28The Impact of Rail Transit Investment on the Residential Property Values in Developing Countries: The Case of Izmir Subway, Turkey(Emerald Group Publishing Ltd., 2006) Çelik, Hüseyin Murat; Yankaya, UğurPurpose The purpose of this paper is to test whether the rail transit investment in Izmir, Turkey has had positive valuation impacts on the surrounding residential properties, and to estimate the value of travel time using relevant parameters. Design/methodology/approach The necessary data were collected via a survey including all real-estate agents in the area. To test the research question, the Hedonic Price Model (HPM) is used as the research technique. The obtained parameters are also used to estimate the value of travel time. Findings The findings of the models has indicated that the proximity to rail stations was valued at $250-300 per meters, and the value of travel per hour was $1.47-1.83 on average. Research limitations/implications These findings should be checked with more consistent database using transaction process, and the mortgage loan rate which was not legislated at the time of study. Practical implications Until a mortgage loan rate is registered in turkey, the estimated parameters can be used in the cost-benefit analysis of rail transit investments in Turkey. Originality/value The theoretical premise that “any improvement in accessibility will be capitalized into the land values” is tested one more time in a developing country case whose urban environment is substantially different from those of the developed world, especially the North American cities. Furthermore, a new methodology using the HPM parameters is also suggested to estimate the value of travel time.Article Citation - Scopus: 31Spatial Interaction Modeling of Interregional Commodity Flows(Elsevier Ltd., 2007) Çelik, Hüseyin Murat; Guldmann, Jean-MichelDrawing from both the spatial price equilibrium theoretical framework and the empirical literature on spatial interaction modeling, this paper expands models of interregional commodity flows (CFs) by incorporating new variables and using a flexible Box-Cox functional form. The 1993 US commodity flows survey provides the empirical basis for estimating state-to-state flow models for 16 commodity groups over the 48 continental US states. The optimized Box-Cox specification proves to be superior to the multiplicative one in all cases, while selected variables provide new insights into the determinants of state-to-state CFs.Article Citation - Scopus: 33Modeling Freight Distribution Using Artificial Neural Networks(Elsevier Ltd., 2004) Çelik, Hüseyin MuratStudies about freight distribution modeling are limited due to the limitations in data availability. Existing studies in this subject, generally either use the conventional gravity models or the regression based models as modeling techniques. The present study, using the 1993 US Commodity Flow Survey Data, models inter-regional commodity flows for 48 continental states of the US with three different artificial neural networks (ANN). The results are compared with those of Celik and Guldmann's (2002) Box-Cox Regression Model. The ANN using conventional gravity model variables provides a slight improvement with respect to this Box-Cox model. However, the ANNs using theoretically relevant variables provide surprising improvements in comparison to the Box-Cox model. It is concluded that ANN architecture is a very promising technique for predicting short-term inter-regional commodity flows.Article Citation - WoS: 5Citation - Scopus: 8Forecasting Interregional Commodity Flows Using Artificial Neural Networks: an Evaluation(Taylor and Francis Ltd., 2004) Çelik, Hüseyin MuratPrevious studies have concluded that the use of artificial neural networks (ANNs) is a promising new technique for modelling freight distribution, supporting, the findings of other studies in the area of spatial interaction modelling. However, the forecasting performance of ANNs is still under investigation. This study tests the predictive performance of the ANN Model with respect to a Box-Cox spatial interaction model. It is concluded that the Box-Cox model outperforms ANN in forecasting interregional commodity flows even if ANN had proven calibration superiority in comparison to conventional gravity type models.