Sürdürülebilir Kalkınma Amaçları
Yayınlar
- MakaleYalnız künye2017An Efficiency Evaluation Model for Academic Faculties of a Leading University by Data Envelopment Analysis
Gul, Muhammet; Yucesan, Melih; Duman, Onur
Data envelopment analysis (DEA) is a linear programming based data analytic method for measuring the relative efficiency of organisational units where the presence of multiple inputs and outputs makes comparisons difficult. Academic departments have critical importance for a university so we agree to research and compare about academic faculties in a leading university in Turkey. The aim of the study is to measure the relative efficiency of the academic faculties and determine the efficient/inefficient ones in the studied university. 12 faculties of the university are investigated within the scope of this study. The input variables are considered as total number of academic staff, total number of non-academic staff, number of students and the output variables are as number of publications, number of projects and the percentage of budget used. While results of CCR model show an average of 90.5% relative efficiency value, five faculties are found 100% efficient according to the CCR model. According to BCC model, the results have an average of 93.7% and 6 faculties are 100% efficient. In terms of the potential improvements evaluated for each inefficient faculty, it is seen that faculty of mechanical engineering and faculty of civil engineering are the ones requiring the most improvement. This paper contributes to the literature a lot however it is a new and proper study on efficiency analysis of faculties of a Turkish university. On conclusion of the DEA efficiency scores, the existence of misallocation of resources or/and inefficient applications to the faculties' academic development are uncovered.
- MakaleYalnız künye2017Estimating Global Solar Radiation for Tunceli City using ANFIS
Celik, Erkan; Gul, Muhammet
Because of the high cost of measurement equipment and their maintenance, global solar radiation measurement is not always implemented. Hence, several forecasting approaches based on fuzzy sets, artificial intelligence or soft computing are proposed to forecast global solar radiation owing to being less cost. However, it is vital to select the most suitable approach for a specific purpose and region. In this study, the adaptive-network based fuzzy inference systems (ANFIS) is proposed to forecast monthly mean daily global solar radiation for Tunceli, Turkey. The monthly data between 1990 and 2010 is used for the proposed approach. The data was obtained from provincial directorate of meteorology of Tunceli. According to the gathered data, the highest value of monthly average daily global solar radiation was measured as 5.218 kWh/m² in the year of 1993. The lowest one with a value of 3.905 kWh/m² belongs to the year of 1997. Similarly, the highest value of monthly average daily sunshine duration was measured as 8.71 hours in the year of 1993. The lowest one with a value of 6.64 hours belongs to the year of 2009. When the data is analysed on a monthly basis, the highest value of monthly average daily global solar radiation was measured as 7.409 kWh/m² in the month of June. The lowest one with a value of 1.762 kWh/m² belongs to the month of December. Similarly, the highest value of monthly average daily sunshine duration was measured as 12 hours in the month of July. The lowest one with a value of 3.1 hours belongs to the month of December. The experiments were applied in MATLAB 7 package software in order to obtain the optimum network architecture. In this network, there are 3 inputs (months, years and monthly average daily sunshine duration) and 1 output (the estimation of the monthly average daily global solar radiation). The ANFIS proposed in this study has Gaussian membership function and twenty fuzzy rules are used. The number of the data points (monthly average daily global solar radiation measurement) is 245. As a performance measure of the ANFIS network, the mean absolute percentage error (MAPE) was used. In testing stage, the MAPE was obtained as 6.365 which is quite well for this type of problem. The coefficient of determination (RSquared) value was calculated as 0.999 which is significantly high. The highly successful results show the success of the fuzzy based methodology of ANFIS which provides estimations of global solar radiation successfully. The presented approach shows that the ANFIS illustrates promising in the forecasting of monthly mean daily global solar radiation using available data. Future studies to estimate the monthly mean global solar radiation of Tunceli city with greater accuracy can be achieved using more apparent meteorological input parameters and different artificial intelligence techniques like artificial neural networks, autoregressive moving average methods or support vector machines. These methods can be improved for available models of daily and hourly estimation of global solar radiation.
AtıfTR Dizin3
İncele - MakaleYalnız künye2017Scopus SJRQ2Occupational health and safety risk assessment in hospitals: A case study using two-stage fuzzy multi-criteria approach
Gul, Muhammet; Ak, M. Fatih; Guneri, Ali Fuat
Occupational Health and Safety (OHS) is a basis to reduce occupational accidents in an acceptable level, and it covers employee health, safety, and welfare in the workplaces. Hospitals as the largest employer group in healthcare industry in Turkey face major hazards categorized as chemical, biological, physical, ergonomic, and psychosocial risks. Although Turkey demonstrates rapid economic growth, OHS practices have not been fully put into practice, and necessary attention has not been paid to the health industry. For this reason, this paper aims to assess risks for health staff, contribute for planning of health services, and enhance regulations. A case study was carried out in a leading hospital in Turkey using a two-stage fuzzy multi-criteria approach, which provides more consistency in decision-making process and gives an appropriate final rank of hazard types. Fuzzy Analytic Hierarchy Process (FAHP) is used in weighing five risk parameters, which are severity, occurrence, undetectability, sensitivity to maintenance non-execution, and sensitivity to personal protective equipment (PPE) non-utilization. The fuzzy VIKOR (FVIKOR) approach is then applied for prioritization of hazard types in each department of the hospital. On conclusion of the hazard control hierarchy, measures are overtaken for the hazards, and areas open for improvement are presented.
AtıfWoS97OpenAlex125
İncele - BildiriYalnız künye2017Forecasting daily patient visits in an emergency department by ga-ann hybrid approach
Pekel, Engin; Gul, Muhammet; Celik, Erkan; Drobne, S.; Zerovnik, J.; Zadnik Stirn, L.; Kljajic Borstar, M.
An Emergency Department (ED) plays a crucial role in the health system by providing acute care for patients who attend hospital without prior appointment. An accurate forecasting of patient visits in EDs contributes to health care decision makers to better allocate ED human resources and medical equipment. In this paper, a hybrid genetic algorithm–artificial neural network (GA–ANN) approach is developed. The forecasting performance of the hybrid approach is obtained using the real-world data set collected from a public hospital in Istanbul, Turkey. The hybrid GA–ANN model is shown to perform well in terms of forecasting accuracy. In order to contribute to the current knowledge, this paper is a novel attempt of applying GA-ANN to model ED patient arrivals, and the results can be used to aid in strategic decision-making on ED resource planning in response to predictable arrival variations.
AtıfScopus4
İncele - Kitap BölümüAçık Erişim2017Use of FAHP for occupational safety risk assessment: An application in the aluminum extrusion industry
Gul, Muhammet; Guneri, Ali Fuat
Risk is dened as relating to a technical or sociotechnical system in which events may take place in the future that have unwanted consequences to assets that we want to protect (Rausand, 2011). The rst stage in controlling risks is to perform a risk assessment in order to see what is required to be done (Health and Safety Executive, 1998). This includes identifying hazards, deciding the harmfulness of them, evaluating all possible risks, reducing them, and recording the results, respectively (Health and Safety Executive, 1998; Main, 2004; Gul and Guneri, 2016). The plentifulness in risk assessment.
AtıfScopus11OpenAlex149İncele - MakaleAçık Erişim2017Scopus SJRQ3Application of artificial neural networks using bayesian training rule in sales forecasting for furniture industry; [Primjena umjetnih neuronskih mreža uz pomoć Bayesova pravila učenja u predviđanju prodaje za industriju namještaja]
Yucesan, Melih; Gul, Muhammet; Celik, Erkan
Most organizations in manufacturing environments aim to increase their profits and reduce costs against competitive and rapidly changing market conditions. Accuracy of sales forecasting is undoubtedly a successful way to reach the aforementioned goals. At the same time, this enables executives to improve customer satisfaction, reduce lost sales and plan production efficiently. As a growing industry in Turkey, furniture manufacturing has an increased product demand in relation to the recent growth in construction and related industries, increase in urban population and increase in person-level income. Therefore, accurate sales forecasting systems in this industry are more focused on the special and calendar factors, such as consumer confidence index, producer price index, time of the year and number of vacation days. In this paper, an artificial neural network (ANN) based forecasting model is proposed by using MATLAB for processing total monthly sales data of a corporate furniture manufacturer located in the Black Sea region of Turkey. The method is a component of ANN, namely Bayesian regularization. The proposed model is applied to monthly sales figures of a corporate furniture manufacturing company. In conclusion, the results of performance measures show that using the ANN model based on Bayesian rules training is an applicable choice for forecasting of monthly sales of the observed furniture factory.
AtıfScopus14WoS11İncele - MakaleYalnız künye2017Scopus SJRQ2Assessment of occupational hazards and associated risks in fuzzy environment: A case study of a university chemical laboratory
Ozdemir, Yasal; Gul, Muhammet; Celik, Erkan
University laboratories involve various occupational hazards during the research and course activities, which might affect health and safety of both researchers and students, including chemical, physical, electrical, mechanical, as well as ergonomic and psychosocial risk factors. There are many aspects open to improvements in Occupational Health and Safety management of laboratories, and it is required to deal with risks, reduce them in an acceptable level, and implement control measures. In this study, a risk assessment approach is proposed for the university laboratory operations. The proposed approach incorporates 5S methodology, failure modes and effects analysis (FMEA), interval type-two fuzzy sets (IT2FSs), analytic hierarchy process (AHP), and the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). AHP is injected into IT2FSs in the phase of evaluation and weighting of severity (S), occurrence (O), and detectability (D) parameters of FMEA. By applying IT2FVIKOR, it is aimed at prioritizing the emerged hazards in the chemical laboratory of the observed university. The proposed approach reveals the important hazards and suggests control measures for managing them. The study methodologically contributes to risk assessment in the knowledge, while a case study in a chemical laboratory of a newly established university offers an insight into education industry in safety improvement.
AtıfScopus89WoS75OpenAlex90İncele - MakaleAçık Erişim2017Scopus SJRQ2A hybrid risk-based approach for maritime applications: The case of ballast tank maintenance
Gul, Muhammet; Celik, Erkan; Akyuz, Emre
Risk assessment is vital for cost-effective ship management in maritime industry since numerous maritime activities pose potential hazards according to the human causalities. Therefore, safety practitioners attempt to offer proactive approaches to mitigate risk as much as possible. In this context, this article presents a hybrid risk-based approach for maritime industry by adopting Fuzzy Analytic Hierarchy Process (FAHP) with fuzzy VIKOR (FVIKOR) methods under Fine-Kinney approach. To illustrate the hybrid risk-based approach, ballast tank maintenance process is handled since there are various hazards causing fatalities, severe injuries, and illness during ballast tank maintenance procedure than any other type of shipboard work. An extensive risk analysis is performed to enhance environment safety and operational reliability in maritime industry. Besides its theoretical contribution, the outcomes of the paper contribute to improve overall safety level of ship by considering potential hazards in risk management.
AtıfScopus73WoS66OpenAlex71İncele - Derleme MakaleYalnız künye2016Scopus SJRQ1A state of the art literature review of VIKOR and its fuzzy extensions on applications
Gul, Muhammet; Celik, Erkan; Aydin, Nezir; Gumus, Alev Taskin; Guneri, Ali Fuat
Multi criteria decision making (MCDM) is one of the research areas of operations research and management science which has widely studied by researchers and practitioners. It finds a compromise solution for evaluating and ranking alternatives from the best to the worst under conflicting criteria with respect to decision maker(s) preferences. In a compromise approach, the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR; that means multi-criteria optimization and compromise solution) continues to be applied satisfactorily across different application areas. This paper conducts a state-of-the-art literature review to categorize, analyze and interpret the current research on VIKOR applications. It also discusses the extensions of VIKOR applied in fuzzy environments. A total of 343 papers are classified into 13 different application areas and a number of sub-application areas. Furthermore, all papers are also categorized with respect to publication year, published journal, country of origin, application type (real case study vs empirical study), and version of fuzzy sets used. This comprehensive literature review provides an insight for researchers and practitioners on VIKOR applications in terms of showing current state and potential areas for future attempts to be focused in the future. (C) 2016 Elsevier B.V. All rights reserved.
AtıfWoS252OpenAlex320İncele - MakaleYalnız künye2016Scopus SJRQ1An artificial neural network-based earthquake casualty estimation model for Istanbul city
Gul, Muhammet; Guneri, Ali Fuat
Earthquakes over the world cause serious damages for people and the economy. The establishment of an appropriate model to estimate potential losses or injuries in earthquake disasters is fundamental to decrease their impacts and losses and effectively respond and mitigate. Turkey as a country that experienced many earthquakes in the last century and had serious human and financial losses needs a comprehensive knowledge of consequences of devastating earthquakes to be able to plan for the future. Artificial neural networks (ANNs) have abilities to solve and analyse complex relations as an appropriate method to estimate number of injuries. In this study, an ANN model is built up for the earthquake casualty prediction, which takes earthquake occurrence time, earthquake magnitude, and population density as the predictors and employs 21 Mw > 5 earthquake disasters occurred in Turkey from 1975 as samples for the training of the network. The model was then tested on a study region consisting of four districts in Istanbul which is estimated to have the highest injury rate according to the earlier reports and generated estimations of the expected number of injured people. Results show that 99.9 % of the variability in the number of injured people is predictable with using this ANN model. Comparison of actual values and estimated output values in the ANN model was also found apparently very close to each other. According to the test case study results, when the value of earthquake magnitude is 6.5 Mw, number of injured people has increased in a sharp trend compared to the previous magnitude value (6 Mw) for all districts. Estimated number of injured people in daytime is obtained higher than at night when the earthquake magnitude is 5 and 5.5 Mw. The highest value in estimated number of injured people has emerged in Fatih district as 7241 for a 7.5 Mw daytime earthquake. On conclusion, it was deduced that the model can reveal accurate estimation of casualties and it can provide information in order to develop mitigation policies, especially in earthquake emergency service management.
AtıfWoS32OpenAlex46İncele - MakaleYalnız künye2016Scopus SJRQ1A fuzzy multi criteria risk assessment based on decision matrix technique: A case study for aluminum industry
Gul, Muhammet; Guneri, Ali Fuat
Decision matrix risk-assessment (DMRA) technique is a systematic approach widely used in the Occupational Health and Safety (OHS) risk assessment. In a typical matrix method approach, a measure of risk value is obtained by evaluating two risk factors as the likelihood of a hazard and the severity of the hazard when it arises. In this paper, a fuzzy approach enabling experts to use linguistic variables for evaluating two factors which are the parameters of matrix method is proposed to deal with shortcomings of a crisp risk score calculation and to decrease the inconsistency in decision making. The parameters likelihood and severity related to the hazards in an aluminum plate manufacturing plant are weighted by using Fuzzy Analytic Hierarchy Process (FAHP), then the orders of priority of 23 various hazard groups are determined by using Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. As a follow-up study of the case application, the proposed risk assessment methodology is applied for hazard types in each department of the plant. Depending on the hazard control hierarchy, control measures are overtaken for the hazards that are placed at first of intra-department rankings. (C) 2015 Elsevier Ltd. All rights reserved.
AtıfWoS145OpenAlex175İncele - MakaleYalnız künye2016Scopus SJRQ1Emergency department performance evaluation by an integrated simulation and interval type-2 fuzzy MCDM-based scenario analysis
Gul, Muhammet; Celik, Erkan; Gumus, Alev Taskin; Guneri, Ali Fuat
Emergency departments (EDs) have an important position in healthcare system environment because of their serviceability to the patients with several illnesses and injuries at all hours of the day and night. Therefore, efficient management of these departments by executives and service providers is only possible with effective tools such as simulation. The concept of multiple criteria decision-making (MCDM) is applicable by computer simulation for decision analysis and performance evaluation of an ED. This study proposes an integration of computer simulation, MCDM methods of interval type-2 fuzzy analytic hierarchy process (IT2FAHP), and ELECTRE for an ED system in a university hospital. Due to the high uncertainty in ED operations, interval type-2 fuzzy sets (IT2FSs) are used in MCDM process. Consequently, the integrated method can be used as a useful tool to evaluate the ED performance and select the best scenario considering different numbers of nurses and doctors for three shifts.
AtıfWoS36OpenAlex42İncele - MakaleYalnız künye2012Scopus SJRQ2A COMPUTER SIMULATION MODEL TO REDUCE PATIENT LENGTH OF STAY AND TO IMPROVE RESOURCE UTILIZATION RATE IN AN EMERGENCY DEPARTMENT SERVICE SYSTEM
Gul, Muhammet; Guneri, Ali Fuat
This paper presents a case study of a discrete-event simulation (DES) model of an emergency department (ED) unit in a regional university hospital in Turkey. In this paper emergency department operations of the hospital were modeled, analyzed and improved. The goal of the study is to reduce patient average length of stay (LOS) and to improve patient throughput and utilization of locations and human resources (doctors, nurses, receptionists). Some alternative scenarios in an attempt to determine optimal staff level were evaluated. These alternative approaches illustrate that vital improvement in LOS and throughput can be obtained by minor changes in shift hours and number of resources. Considering future changes in patient demand a scenario which reduces LOS and improves throughput is available in the paper. Significance: The Key Performance Indicators (KPIs) to determine and improve system performance in healthcare emergency departments consist of to reduce patient average length of stay (LOS), to improve patient throughput and resource utilization rates. Alternative scenarios and optimal staff levels are enhanced within the scope of this study.
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