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Öğe Analyzing the Causes of Deforestation with Statistical Quality Control Methods in Turkey(Ankara Bilim Üniversitesi, 2024) Erdoğan, Melike; Torman, RabiaThe forests that cover the earth are the main source of everything for living things. The sustainability of forests is of great importance for ecosystems, biodiversity, erosion prevention, climate diversity, tourism, protection of global balance and water resources. Today, forests are subject to change and destruction among the resources on earth. As a result of human interventions and actions, forests are damaged unpredictably. With the combination of many reasons, the negative concept called deforestation has come to the agenda as an issue that is increasingly attracting attention today. Deforestation is a problem that should be discussed, studied and urgent solutions should be sought for Turkey. In this study, the causes of deforestation in Turkey are examined and analyzed using statistical quality control methods. In this context, the effects of agricultural activities, forest crimes, forest fires, global warming and climate change, urbanization and overpopulation on deforestation have been investigated. Whether the causes are statistically under control or not are analyzed, out-of-control points are identified with the help of control charts and suggestions are presented for the elimination of these causes. The causes of deforestation have been evaluated using MINITAB software with the help of systematic statistical quality control tools. With the effect of the study, it is aimed to develop awareness in cooperation with the authorities and society and to determine relevant actions to prevent deforestation. By identifying the reasons that cause most to deforestation, policies are revealed to eliminate the problem of deforestation in Turkey. With this paper, it is foreseen that the actions to be taken regarding deforestation in the forest area of Turkey will have an impact on the global forest area and will create an international awareness and example and will serve as a guiding study for decision-makers.Öğe Assessing farmers' perception to Agriculture 4.0 technologies: A new interval-valued spherical fuzzy sets based approach(Wiley, 2022) Erdoğan, MelikeAgriculture 4.0 is the usage of advanced technologies for ensuring sustainability and efficient use of resources in agriculture, which can be accepted one of the biggest challenges of mankind. With Agriculture 4.0 technologies, it is aimed to raise productivity, reduce waste and costs. To ensure that agriculture 4.0 technologies are adopted by farmers as soon as possible, the perspective and perception of farmers to these technologies should be analyzed firstly. For this purpose, we propose a decision-making framework to measure farmers' view of Agriculture 4.0 technologies and to perform a prioritization study based on the perception of use among these technologies. Multicriteria decision analysis is also utilized to deal with all qualitative and quantitative factors in the decision process. Within the scope of this study, interval-valued spherical fuzzy numbers are used to model the vagueness in the process in the best manner and to be able to reflect the uncertainty arising from the usage of linguistic variables in the decision process. The SWARA and MAIRCA multicriteria decision making (MCDM) methods, which have been used frequently in the literature and are applied very successfully in MCDM problems, have been firstly extended by spherical fuzzy sets (SFSs) and the advantages for these methods have been utilized within the framework of fuzzy logic. The proposed method allows decision-makers to mirror their hesitations in decision-making using a linguistic evaluation scale established upon interval-valued SFSs. A comparative analysis based on the ordinary fuzzy sets is also performed for the obtained results and the clear superiority of the proposed approach is presented. In addition, the robustness of the model is tested with sensitivity analysis. After these analyzes it is obtained that this paper provides a unique perspective to the literature due to its originality in both the subject and adopted fuzzy methodology.Öğe Comparison of hospital service performances under COVID-19 pandemics for pilot regions with low vaccination rates(Pergamon-Elsevier Science Ltd, 2022) Erdoğan, Melike; Ayyıldız, ErtuğrulIt is essential to measure the quality and performance of health centers and propose policies in order for health services to continue without interruption during the pandemic period and for the continuous and proper implementation of new procedures in hospitals with COVID-19.The measurement of service quality and performance in hospitals should be provided not only for the smooth flow of health services that are vital for individuals but also for the elimination of hesitations in the treatment and vaccination processes related to COVID-19. Previously, models have been proposed by introducing some criteria to measure and evaluate hospital service performance in some extraordinary conditions, but such a study has not yet been put forward under pandemic conditions. Starting from this point, we aim to fill the gap in the literature by conducting a measurement study for hospitals in the pilot region, where COVID-19 cases are common but vaccination is observed at low rates. For this aim, the evaluation criteria are gathered under basic dimensions as in SERVPERF (Service Performance), which is a widely used tool for measuring service quality and a fuzzy multi-criteria decision analysis is proposed to measure the service performance of state hospitals for a pilot region. In the proposed methodology, the integrated methods consisting of CRITIC-TOPSIS have been extended with fermatean fuzzy sets. Expert opinions are taken via questionaries to determine hospital service performances. Based on the results obtained from the hospitals in the pilot region, the policies and strategies to be adopted by the hospitals serving under pandemic conditions worldwide to increase the service quality have been put forward. Additionally, the sensitivity of the parameters in the problem is measured, and then the validity of the obtained results is also validated. According to the results, assurance is determined as the most important main service performance factor during the pandemic period. So, the managers should develop strategies to address people's concerns about vaccines and increase people's trust in hospitals.Öğe A comprehensive analysis of the causal factors in repair, maintenance, alteration, and addition works: A novel hybrid fuzzy-based approach(Pergamon-Elsevier Science Ltd, 2022) Mohandes, Saeed Reza; Karaşan, Ali; Erdoğan, Melike; Sabet, Pejman Ghasemi Poor; Mahdiyar, Amir; Zayed, TarekDespite the recent improvements made to the area of occupational health and safety (OHS) within the con-struction sector, the Repair, Maintenance, Minor alteration, and Addition (RMAA) works have been given scant attention. In this study, given the significance of the injuries reported in the RMAA sector, a meticulous inves-tigation is conducted into the causal factors contributing to the related accidents by capturing their causal in-terrelationships together with their importance levels. To this end, first, a comprehensive list of factors contributing to RMAA accidents was obtained through an extensive literature review and experts' interviews. Then, through the lenses of qualified relevant experts in Hong Kong, the proposed interval-valued intuitionistic fuzzy (IVIF) DEMATEL and IVIF analytic network process were employed to respectively uncover the cause-and -effect relationships among these factors and prioritize them. The findings show that the lack of assessment and praising of workers' OHS understanding and performance, the high turnover rate of workers resulting in difficulties in providing safety training and education, and lack of safety training for workers are the most critical causes to be given full attention by construction safety managers. The methodological approach proposed in this study brings about two theoretical contributions: unraveling interrelationships existing among the causal factors, and prioritization of them considering their interrelationships. The findings reported in this study also aid decision-makers in improving the critical causal factors in a way to enhance the OHS of RMAA sector.Öğe Evaluating blockchain risks by using a MCDM methodology based on pythagorean fuzzy sets(Springer Verlag, 2020) Özkan, Betül; Kaya, İhsan; Erdoğan, Melike; Karaşan, AliUsing 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.Öğe 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, MuratMilitary 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.Öğe A fuzzy based MCDM methodology for risk evaluation of cyber security technologies(Springer Verlag, 2020) Erdoğan, Melike; Karaşan, Ali; Kaya, İhsan; Budak, Ayşenur; Çolak, MuratCyber 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.Öğe Healthcare service quality evaluation: An integrated decision-making methodology and a case study(Elsevier Science Inc, 2022) Karaşan, Ali; Erdoğan, Melike; Çınar, MelihDevelopments and changes in health services give importance to the concept of competition and encourage to increase quality among the healthcare centers. During these processes, the most required expectations from the system are achieving the desired quality and maintenance of the system environments. In this sense, measurement and continuous improvement of service quality are crucial for health centers to provide better service to patients. For this aim, this paper presents an integrated assessment methodology based on the distance-based Pythagorean Fuzzy Multiple Criteria Decision Making (MCDM) method, TOPSIS, and Fuzzy Inference System (FIS) for the measurement of health care service quality. To show the efficiency of the proposed method, a case study is carried out by comparing the ten clinics of a private hospital. Five dimensions of service quality (SERVQUAL) have been used as the main criteria for evaluating the service quality levels of the clinics, and multiple sub-criteria are determined for each dimension for a detailed analysis. Pythagorean Fuzzy TOPSIS is executed to the determined decision matrices to obtain inputs of the fuzzy rule-based system. Then, the clinic's service quality levels are calculated by implementing the fuzzy inference system. Moreover, sensitivity analyses based on the changes in the decision makers' weights are also applied to check the flexibility of the results. Finally, implementations with respect to theoretical, managerial, and policy aspects are discussed based on the obtained results.Öğe Identifying and prioritizing the factors to determine best insulation material using Bayesian best worst method(Sage Publications Ltd, 2022) Ayyıldız, Ertuğrul; Erdoğan, MelikeThe issue related to energy efficiency is being addressed worldwide as a subject that is becoming more and more important every day. The implementation of insulation measures for buildings, which is one of the most crucial measures of energy consumption, is a critical issue that can be applied to both increase efficiency and reduce the greenhouse gas effect. While trying to create buildings that are efficient in terms of energy consumption, the sustainability factor should always be paid regard primarily. Since different insulation materials are used in the building insulation process, it is necessary to consider many factors in the evaluation of these materials. The complex nature of the selection of insulation materials problem requires a multi-criteria decision approach to apply a detailed and systematic evaluation. Considering all of these, it is aimed to evaluate the building insulation materials under the sustainability perspective by using the Bayesian best worst method in this paper. As a result, the weights are calculated and ranking of the criteria is obtained and finally, the most and least important factors are revealed for the building insulation selection problem. The economic and performance criteria are determined as the most important to determine the best insulation material.Öğe Investigation of the pharmaceutical warehouse locations under COVID-19-A case study for Duzce, Turkey(Pergamon-Elsevier Science Ltd, 2022) Erdoğan, Melike; Ayyıldız, ErtuğrulPharmaceutical warehouses are among the centers that play a critical role in the delivery of medicines from the producers to the consumers. Especially with the new drugs and vaccines added during the pandemic period to the supply chain, the importance of the regions they are located in has increased critically. Since the selection of pharmaceutical warehouse location is a strategic decision, it should be handled in detail and a comprehensive analysis should be made for the location selection process. Considering all these, in this study, a real-case application by taking the problem of selecting the best location for a pharmaceutical warehouse is carried out for a city that can be seen as critical in drug distribution in Turkey. For this aim, two effective multi-criteria decision-making (MCDM) methodologies, namely Analytic Hierarchy Process (AHP) and Evaluation based on Distance from Average Solution (EDAS), are integrated under spherical fuzzy environment to reflect fuzziness and indeterminacy better in the decision-making process and the pharmaceutical warehouse location selection problem is discussed by the proposed fuzzy integrated methodology for the first time. Finally, the best region is found for the pharmaceutical warehouse and the results are discussed under the determined criteria. A detailed robustness analysis is also conducted to measure the validity, sensibility and effectiveness of the proposed methodology. With this study, it can be claimed that literature has initiated to be revealed for the pharmaceutical warehouse location problem and a guide has been put forward for those who are willing to study this area.Öğe A NEW APPROACH FOR RULE ESTIMATION OF FUZZY INFERENCE SYSTEM: A CASE STUDY FOR PUBLIC TRANSPORT MAINTENANCE SYSTEM(2020) Erdoğan, Melike; Kaya, İhsanThe 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.Öğe A New Fuzzy Approach for Analyzing the Smartness of Cities: Case Study for Turkey(2021) Erdoğan, MelikeSmart cities, developed as alternative to classical urbanism, are areas where information andcommunication technologies are used to make places more livable, sustainable and efficient. Ifa city offers solutions to problems related to governance, people, economy, mobility,environment and living issues, it can be defined as "smart city". The smartness of cities can bemeasured on these six basic axes. By analyzing the smartness of cities, evaluations can be madeon the quality of life, health, public safety, environment and services. Hereby, appropriatemeasures can be taken against problems and strategies can be developed to increase thesmartness of cities. This paper proposes a new decision making analysis to evaluate andcompare the smartness of cities. For this aim, we considered the cities which are the candidatesto be smart areas in Turkey. At this point, we applied multi-criteria decision-making (MCDM)analysis to evaluate criteria and alternatives in the decision process. We also utilized from fuzzylogic to model the uncertainty in the best way. Furthermore, we applied extended version ofordinary fuzzy sets which is named spherical fuzzy sets for the first time with QUALIFLEXmethod. Thus, one of the most comprehensive qualitative analyses ever made in the evaluationof smart cities is revealed and the usability of spherical fuzzy sets by MCDM methods isdemonstrated. In addition, a sensitivity analysis was used to examine the robustness of theproposed method. As a result, a novel fuzzy decision-making approach has been proposed inthe evaluation of smart cities.Öğe Prioritizing the Factors for Customer-Oriented New Product Design in Industry 4.0(2020) Erdoğan, Melike; Bilişik, Özge NalanCustomer-oriented new product design is one of the most important processes in the production environment to improve product quality and reliability and maximize their productivity. It is also necessary to consider customer expectations in this process for an effective design. In this paper, we present a methodology which is called Pythagorean Fuzzy Analytic Hierarchy Process (PF-AHP) for prioritizing criteria which should be considered for an efficient customer-oriented new product design in Industry 4.0 transition primarily. We use Pythagorean Fuzzy Sets (PFSs) to allow experts to make more flexible evaluations and handle the uncertain and vague information in a wider way. We determine five main and eighteen sub-criteria that affect the new product design process and after applying PF-AHP, we find that the most important main-criterion determined as “Production” and sub-criterion determined as “Return on Investment”.Keywords: Industry 4.0, Multi-Criteria Decision Making, Product Design, PFSsÖğe Risk analysis of the autonomous vehicle driving systems by using pythagorean fuzzy AHP(Springer Verlag, 2020) Karaşan, Ali; Kaya, İhsan; Erdoğan, Melike; Budak, AyşenurAutonomous 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.Öğe 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, MelikeY 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.
