SUMMARYEfficient management of public transportation systems is one of the most important requirements in rapidly urbanizing world. Forecasting the demand for transportation is critical in planning and scheduling efficient operations by transportation systems managers. In this paper, a time series forecasting framework based on Box-Jenkins method is developed for public transportation systems. We present a framework that is comprehensive, automated, accurate, and fast. Moreover, it is applicable to any time series forecasting problem regardless of the application sector. It substitutes the human judgment with a combination of statistical tests, simplifies the time-consuming model selection part with enumeration, and it applies a number of comprehensive tests to select an accurate model. We implemented all steps of the proposed framework in MATLAB as a comprehensive forecasting tool. We tested our model on real passenger traffic data from Istanbul Metro. The numerical tests show the proposed framework is very effective and gives higher accuracy than the other models that have been used in many studies in the literature.

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Fishing ports are the vital constituent of the fishery industry of Turkey. With governmental contribution, the number of the fishing ports reached to 366 alongside of the shores and the collected fish volume h as been in increasing trend. However, there are differences in the location characteristics and technical infrastructure so that each facility's success level is measured differently with convenient parameters. To increase the performance of fishing ports, for their better utilization, and also to understand which of them can be transformed to regional centers a classification is needed. With the transformation to the regional centers, i.e. the infrastructure improvements of the facilities and providing multiple services such as tourism and transportation activities; the efficiency of the ports can be increased. In this paper, a classification methodology is developed and it is tested. While applying the methodology, expert workshops are carried out to represent current fishery environment in Turkey. In the meetings, decision criteria are discussed by participating over 200 experts in the field. f-AHP and GIS/Spatial Analysis is used to analyze spatial suitability. Results of the study showed that the methodology is capable of dealing with spatial and non-spatial characteristics of the data-set and determine the convenient alternatives.

Recreational fishing, sailing, activities involving boating are parts of the social life-style which family members practices outdoors as social activities throughout the counties where maritime is common. It is being observed that, these kinds of activities tend to improve in Turkey within the recent years for the reasons like the increase in the national income and acculturation. Consequently, in order for satisfying this demand, new mooring areas with reasonable costs are required. In order to fulfill the berthing and mooring needs of the vessels, cost efficient and environmental solution approaches are need. This article aims to develop a system offering for constitution of sustainable policies with regards to determination of boats berthing and mooring areas that are needed for amateur marine in Turkey. For that reason, geographic information system (GIS) based approaches are taken into consideration for spatial analysis, which is used to specify suggested facilities regarding any component that generates the system. The results showed that the suggested method successfully functions regarding the selection of facility location, and it has been detected that by the suggested system approach, it is possible to achieve new and higher capacities.

Hot spots can be described as the high attraction points. Defining the hot spots and clustering approaches in a metropolitan area helps to provide solutions for balancing the freight flows between the sub-areas in the city center. It also helps to provide solutions for secondary problems, such as traffic congestion and air pollution. The technique assists decision-makers in making inferences about the city's future and taking precautions for sustainability. In this paper, a geographic information systems (GIS) analysis tool, spatial statistics based on the Getis Ord* statistics, is used to illustrate which part of Istanbul has hot spots. The hot spot identification is based on logistics activities at the locations of the logistics facilities. The outputs of the analysis are discussed within the context of logistics costs and environmental effects.Anahtar Kelimeler: Mağaza yeri seçimi, delphi tekniği, makro analiz, mağaza yeri seçim kriterleri