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Transport energy demand (TED) forecasting is a crucial issue for countries like Turkey that are dependent on external resources. The accuracy and effectiveness of these forecasts are extremely important, especially for the strategies and plans to be developed. With this in mind, different forms of forecasting models were developed in the present study using the Walrus Optimizer (WO) and White Shark Optimizer (WSO) algorithms to estimate Turkey's energy consumption related to road and railway transportation modes. Additionally, another objective of this study was to examine the impacts of different transport modes on energy demand. To investigate the effect of demand distribution among transport modes on energy consumption, model parameters such as passenger-kilometers (P-km), freight-kilometers (F-km), carbon dioxide emissions (CO2), gross domestic product (GDP), and population (POP) were utilized in the development of the models. It was found that the WO algorithm outperformed the WSO algorithm and was the most suitable method for energy demand forecasting. All the developed models demonstrated a better performance level than those reported in previous studies, with the best performance achieved by the semi-quadratic model developed with the WO, showing a 0.95% MAPE value. Projections for energy demand up to the year 2035 were established based on two different scenarios: the current demand distribution among transport modes, and a demand shift from road to rail transportation. It is anticipated that the proposed energy demand models will serve as an important guide for effective planning and strategy development. Moreover, the findings suggest that a balanced distribution among transport modes will have a positive impact on transport energy and will result in lower energy requirements. [ABSTRACT FROM AUTHOR]

In this study, a hybrid traffic signal control (HTSC) system based on phase and time optimization was developed. The Flower Pollination Algorithm (FPA) approach was used for phase optimization, while Type-2 Fuzzy Logic, optimized with the Crow Search Algorithm (CSA), was utilized for time optimization. The hybrid system's performance was investigated using nine different traffic conditions and four different intersection geometries. The hybrid system was compared with three controller systems which are a fixed-time signal controller, a signal controller based on the FPA approach (FPA_TSC), and the optimized Type-1 fuzzy logic signal controller (Type-1 FL-TSC). The HTSC approach achieved the best performance with about 32% improvement over the fixed-time traffic controller and it showed 5% and 6% better performance than the FPA_TSC and Type-1 FL-TSC, respectively. Considering the performance of the new hybrid system, it is effective in minimizing delays and driver dissatisfaction occurring from signalization. It also contributes to the reduction of emissions and fuel consumption. The HTSC approach can be used as an alternative signal control method in the control of intersections with high traffic volume due to its fast and effective performance. [ABSTRACT FROM AUTHOR]

In this study, it is aimed to examine the effectiveness of the internal control systems of participation banks and the relationship between them and the level of institutionalization, and also to reveal whether the internal control system has an effect on the level of institutionalization. In this context, a questionnaire was applied to the employees of the participation bank operating in Turkey. The data obtained were analyzed with the SPSS program. As a result of the research, it has been determined that the efficiency of the internal control systems and internal control components of the participation banks and the level of institutionalization are at a medium level. A positive correlation was found between the internal control system and its components and the level of institutionalization. It has been determined that there is a strong relationship between the internal control system, control environment, information and communication components and the level of institutionalization in participation banks. In addition, a medium level relationship was determined between risk assessment, control activities and monitoring components and institutionalization. It has been determined that the internal control system and its components have a positive effect on the level of institutionalization of participation banks. [ABSTRACT FROM AUTHOR]

In this study, Bezier search differential evolution (BeSD) and black widow optimization (BWO) algorithms-based estimation models in different forms have been developed to estimate the transportation energy consumption in Turkey. In order to examine the effect of demand distribution in modes of transportation on energy consumption, parameters in modes of transportation which are Passenger-km and Freight-km, Carbon dioxide emissions, Gross Domestic Product and Infrastructure Investment parameters are used as model parameters. Model performances are evaluated within different error criteria, and their performances are revealed. The BeSD algorithm performed better than the BWO algorithm and revealed that it is the most appropriate method for transportation energy demand (TED) estimation. Although each model developed using two different approaches is usable, BeSD-based quadratic model has shown the highest performance with a 0.95% MAPE value, and TED's predictions for the future have been put forth based on this model. According to two different scenarios, TED projections until 2040 are presented for cases in which the current distribution of demand in modes of transportation and there is a demand shift from highway to other modes of transportation. The projections of the parameters have been determined by the least squares method. In the first scenario, it has been predicted that there will be 63 MTOE energy demand in 2040, and the projection values are consistent with the Ministry of Energy and Natural Resources values. In the second scenario, when demand shifts from the highway to other modes of transportation, it is predicted that energy consumption will decrease and there will be 42 MTOE in 2040. [ABSTRACT FROM AUTHOR]

The purpose of this study is to develop a control system that optimizes the phase plan, sequence and signal timing using the flower pollination algorithm (FPA). At the same time, it is aimed to improve the fixed-time control system with the optimum cycle length search approach based on the differential evolution algorithm. The applicability and performances of these two control systems were examined in 15 different traffic situations according to 4 different intersection geometries. Fixed-time and optimized fuzzy logic traffic controller (FLC) developed by Dogan were used as the reference control systems in performance comparison. The optimum cycle length search system can achieve approximately 18% improvement over the fixed-time system, but showed lower performance than the FPA and FLC control systems. The FPA system has proven its applicability by achieving the best performance with about a 30% improvement compared to the fixed-time system and about 3% improvement compared to the FLC system. The FPA approach, which has a fast and effective performance, has been found to be an alternative method for intersection control, and it is foreseen that it can increase the intersection capacity and reduce the negative effects such as delay and fuel consumption. [ABSTRACT FROM AUTHOR]

Delay is a significant research topic since it includes indicators such as travel quality, lost time and fuel consumption. Furthermore, the delay is used for optimization of traffic control systems and determination of the level of service at signalized intersections. Therefore, researchers have focused on accurate estimation of delay. The objective of this study is to simply and accurately estimate the delay and evaluate the performance of the proposed approaches which are artificial bee colony (ABC) and flower pollination algorithms (FPA). In this study, ABC and FPA have been used to develop different delay models which are linear, semi-quadratic, quadratic and power forms. Analysis period (T), the green ratio (g/C; effective green to cycle length) and the degree of saturation (x = v/c; volume to capacity) are used as input parameters while developing the models. The results of present models are compared to estimations obtained from analytical models which are Highway Capacity Manual and Australian (Akçelik) delay models. Semi-quadratic form yielded to best results in terms of coefficient of determination (R2), mean square error and mean absolute error. Additionally, FPA approach showed better performance than ABC approach finding the optimal solution in the lower number of iterations. [ABSTRACT FROM AUTHOR]

This study proposes a new optimization technique to estimate the Transportation Energy Demand (TED) employing the Flower Pollination Algorithm (FPA). The TED estimation models were developed based on three parameters, which are Annual Vehicle-Km (AVK), Gross Domestic Product per Capita (GDPperC), and Carbon-dioxide (CO2) emission according to the linear, power and quadratic forms. These three parameters were determined by the WEKA data mining software program among nine parameters. Randomly selected 80% of historical data for 47 years, from 1970 to 2016, were used for the training of the algorithm, and the remains were used in the testing stage of the models. The performances of the models were evaluated according to six different statistical criteria. Transportation energy demand forecasts by 2035 were carried out using three different scenarios using the TED estimation models. According to the scenarios, it is predicted that the transportation energy demand in Turkey will have doubled by 2035 in comparison with 2016. The FPA approach has been successfully applied in the development of the TED estimation models. The most important impact of this study is to help the creation of strategic action plans for energy policies in the transport sector and to contribute to the more efficient use of limited energy resources in the country. [ABSTRACT FROM AUTHOR]

Delay is an important parameter in the optimization of traffic signals and the determination of the level of service (LOS) of a signalized intersection since it directly reflects the lost travel time and fuel consumption. The accurate estimation of delay is, therefore, an important issue. The purpose of this study is to develop new delay models with less input parameters by using one of the artificial intelligent techniques. In this research, three types of differential evolution delay estimation models (DEDEM), i.e. linear, exponential and quadratic, were developed using differential evolution (DE) approach. In developing of the delay models, the green ratio (g/C effective green to cycle length) and the degree of saturation (x=v/c; volume to capacity) were considered. The first one changed from 0.35 to 0.60, the second one varied between 0.7 and 1.4. The model outputs were compared analytically to the HCM and Australian (Akçelik) delay models. The study results illustrated that R2, Mean Square Error (MSE) and Mean Absolute Error (MAE) values of DEDEMquadratic, which are 0.97, 207.98, 12.12 respectively, were better than analytical delay models and other types models. As a result, the quadratic form of DEDEM model can be used as an alternative estimation model for delay, and DE approach can be utilized as a model-fitting algorithm as well. [ABSTRACT FROM AUTHOR]

Independent auditing is a necessary process for establishing an environment of trust for both businesses and investors. Therefore, the need for independent auditing and the number of independent audit companies have increased. The quality of the service provided by independent audit companies for businesses and the ranking of audit companies within the framework of this quality have gained importance. This study aims to rank the independent audit companies operating in Turkey, excluding the four big independent audit companies, using multi-criteria decision-making techniques according to audit quality and revenue performance criteria, in line with the information obtained from the transparency reports published between 2017 and 2021. In addition, one of the aims of the study is to make due diligence on the transparency reports published by independent audit companies. To rank in the study, we determined the criteria for the number of responsible auditors of the independent audit companies, the duration of the annual training given to the auditors, the income the company derives from independent audit services, the income obtained from audit, and assurance services other than independent auditing, the income obtained from non-audit services, and the number of Public Interest Organizations. According to the Public Disclosure Platform data, the universe of the research consists of 86 independent audit companies operating in Turkey in 2022. Four big independent audit companies and companies that do not have transparency reports or that have missing information in their transparency reports were excluded from the scope of the study, and the information of 28 independent audit companies with full working data was used. According to the CRITIC method, the most important criterion is the number of engagement partners, and other criteria are determined as training time, income from independent audit services, income from other auditing and assurance services, income from non-audit services, and the number of Public Interest Organizations. According to the COPRAS method, the top three independent audit companies are AAC, MERIDYEN, and GÜRELİ; the last three independent audit companies are listed as MBK, DMF, and ARILAR. In addition, it has been determined that transparency reports are not prepared within a standard, and there are differences, especially in terms of content. [ABSTRACT FROM AUTHOR]