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    Evaluating blockchain risks by using a MCDM methodology based on pythagorean fuzzy sets
    (Springer Verlag, 2020) Özkan, Betül; Kaya, İhsan; Erdoğan, Melike; Karaşan, Ali
    Using blockchain technology (BT) in companies has become more common nowadays. But implementing a new BT contains many risk factors from different perspectives. Some of these risks can be critical for companies’ processes. These risks should be carefully identified and analyzed to minimize the negative effects of them. Evaluation of the risks can be considered as a multi criteria decision making (MCDM) problem. In this study, the risks that can occur when implementing BT are evaluated by using a MCDM methodology based on Pythagorean fuzzy analytic hierarchy process (PF-AHP). By using Delphi method, the risks are determined and the problem is constructed as a hierarchical form. After that, the risks are prioritized by using PF-AHP and the most important risks are obtained. The main aim of this paper is to help companies to determine which risks are more critical and to which of them should be given more priority during BT implementation. © 2020, Springer Nature Switzerland AG.
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    Evaluation of defense strategies by using a MCDM methodology based on neutrosophic sets: A case study for Turkey
    (Springer Verlag, 2020) Karaşan, Ali; Kaya, İhsan; Erdoğan, Melike; Özkan, Betül; Çolak, Murat
    Military operations are vital activities that are involving many risks from different perspectives. Although these operations are carried out for multiple purposes which can be classified as the minimum damage that is taken and the maximum damage that is given. The officers who are responsible for the strategy determination for the operations are one of the most effective factors of the results. Since the system has multi experts, multi criteria and many alternatives, it is suitable to apply a multi criteria decision making (MCDM) methodology for the decision-making process. In this study, defence strategies are evaluated with respect to the determined criteria based on the decision makers’ judgements by using CODAS method based on Neutrosophic Sets that can be able to manage both qualitative and quantitative data. © 2020, Springer Nature Switzerland AG.
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    A fuzzy based MCDM methodology for risk evaluation of cyber security technologies
    (Springer Verlag, 2020) Erdoğan, Melike; Karaşan, Ali; Kaya, İhsan; Budak, Ayşenur; Çolak, Murat
    Cyber security that also known as information technology security is to protect computers, mobile devices, servers, electronic systems and networks from malicious digital attacks. In recent years, cyber security threats have been a growing problem for any critical digital infrastructure and various cyber-attacks created over the Internet are also becoming a big issue for the society. Therefore, the use of technologies developed to provide cyber security is very important. However, the risks of cyber security technologies should be taken into account when choosing among cyber security technologies. For this aim, we have proposed a multi-criteria decision making (MCDM) methodology based on hesitant fuzzy sets (HFSs) that gives experts extra flexibility in using linguistic terms to evaluate the criteria and alternatives to determine the best cyber security technology. For this aim, a study has also been discussed which deals with risk factors in the selection of cyber security technologies via fuzzy MCDM process. © 2020, Springer Nature Switzerland AG.
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    A NEW APPROACH FOR RULE ESTIMATION OF FUZZY INFERENCE SYSTEM: A CASE STUDY FOR PUBLIC TRANSPORT MAINTENANCE SYSTEM
    (2020) Erdoğan, Melike; Kaya, İhsan
    The increase in the population and the high amount of individual vehicle usage in the big cities brought traffic congestion and environmental problems. Additionally, these issues have also some negative effects on the public transport systems (PTSs). In this respect, the analysis of PTS is critical and important for both city life and people. It is possible that the failures in PTS can lead to many problems. Disruption of daily life, loss of lives and property or damage to the environment are only just a few of these problems. In this context, effective maintenance planning for PTSs is so crucial. In this study, the rule estimation for a fuzzy rule-based system (FRBS) which takes into consideration many factors for the maintenance planning of PTSs is discussed. The rule-based system for maintenance planning of Bus Rapid Transit System (BRT) will be highly effective for the prediction of failures for PTSs and the correct actions to be taken. Rule estimation for this system is aimed to increase the precision and flexibility of maintenance procedures. In this context, a model based on artificial neural networks (ANNs) has been developed and used in rule estimation for FRBS. For this aim, ten cases that are not in the rule base system are estimated and the results of the fuzzy rule-based maintenance inference system for the relevant inputs are revealed. Thus, it has been shown that ANNs can be used effectively for the analysis of rules that are not included in the current rule-based maintenance system.
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    Risk analysis of the autonomous vehicle driving systems by using pythagorean fuzzy AHP
    (Springer Verlag, 2020) Karaşan, Ali; Kaya, İhsan; Erdoğan, Melike; Budak, Ayşenur
    Autonomous driving system (ADS) is a combination of different components those can be composed as operations of the automobile and decision making mechanisms both in regular time and unexpected situations. These operations are performed by a virtual driver to carry out the objectives that are determined by the users. The main advantages of ADS are to free the drivers from attention states which are presented by American Automobile Association Foundation (AAAF). At the same time, there are some safety risks for these systems those need to be tested and solved. In this paper, we analyzed ADS to prioritize risks by using Pythagorean fuzzy sets (PFSs) that can be used to represent uncertainty in decision process. For this aim, a methodology based on Pythagorean analytic hierarchy process (PAHP) has been suggested. By the way, the Hazard Analysis and Risks Assessment introduced in the ISO 26262 standards are taken as a basis for risk evaluation. © 2020, Springer Nature Switzerland AG.
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    Two-phase multi-expert knowledge approach by using fuzzy clustering and rule-based system for technology evaluation of unmanned aerial vehicles
    (Springer London Ltd, 2022) Çolak, Murat; Kaya, İhsan; Karaşan, Ali; Erdoğan, Melike
    Y Unmanned aerial vehicles (UAVs) are utilized in many different areas for different aims such as the benefit of humanity, safety control, traffic control, crop monitoring, scientific research, and commercial applications. Moreover, the UAVs are also successfully utilized for military operations, such as surveillance of an area and counter-terrorism actions. Evaluating them through the technological perspective is quite significant and should be considered from multiple perspectives. In this context, it will be more beneficial to construct a methodology for an efficient evaluation process. The fuzzy set theory (FST) can also be integrated into this methodology to improve its sensitiveness and flexibility. In this paper, a novel methodology integrating fuzzy c-means (FCM) clustering and fuzzy inference system (FIS) has been suggested for the technical evaluation of UAVs. While the FCM clustering algorithm has been utilized to determine the clusters, rules have been created for the FIS through expert assessments, and alternative UAV technologies have been prioritized. For the evaluation procedure, the hierarchical structure of the technology evaluation features has been determined by fusing expert knowledge, literature review, and related ISO standards. Through the FCM clustering algorithm, alternative vehicles have been clustered based on the sub-features of each main feature. Then, FIS has been conducted by using experts' knowledge from the fields of military technologies in UAVs and armed UAVs to obtain the technology indices of the eight UAVs locally produced and used in Turkey. The results demonstrate that the proposed methodology can be successfully applied by the managers or research and development (R&D) engineers for evaluation of the UAV technologies to consider cardinal and linguistic data. Additionally, a comparative analysis based on self-organizing map (SOM) and fuzzy k-means algorithms has also been applied for the proposed method, and their performances have been compared.