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Article Citation - WoS: 76Citation - Scopus: 73Measuring the Efficiency of Hospitals: a Fully-Ranking Dea-Fahp Approach(Springer, 2019) Rouyendegh, Babak Daneshvar; Oztekin, Asil; Ekong, Joseph; Dag, AliThe goal of this study is to present a DEA-based fuzzy multi-criteria decision making model for firms in the health care industry in order to enhance their business performance. The study demonstrates a real-life use of the proposed model, mainly designed for hospitals. Data envelopment analysis enhanced with fuzzy analytic hierarchy process are collectively utilized to quantify the data and structure the model in decision-making. The juxtaposition of the two methods is used to compile a ranked list of multiple proxies containing diverse input and output variables which occur in two stages. This hybrid model provides several benefits, one of which is the ability to make the most appropriate decision considering the value of the weights determined by the data from the hybrid model.Article Citation - Scopus: 43Development of an Intelligent Tutoring System Using Bayesian Networks and Fuzzy Logic for a Higher Student Academic Performance(MDPI AG, 2020) Eryilmaz,M.; Adabashi,A.In this experimental study, an intelligent tutoring system called the fuzzy Bayesian intelligent tutoring system (FB-ITS), is developed by using artificial intelligence methods based on fuzzy logic and the Bayesian network technique to adaptively support students in learning environments. The effectiveness of the FB-ITS was evaluated by comparing it with two other versions of an Intelligent Tutoring System (ITS), fuzzy ITS and Bayesian ITS, separately. Moreover, it was evaluated by comparing it with an existing traditional e-learning system. In order to evaluate whether the academic performance of the students in different learning groups differs or not, analysis of covariance (ANCOVA) was used based on the students' pre-test and post-test scores. The study was conducted with 120 undergraduate university students. Results showed that students who studied using FB-ITS had significantly higher academic performance on average compared to other students who studied with the other systems. Regarding the time taken to perform the post-test, the results indicated that students who used the FB-ITS needed less time on average compared to students who used the traditional e-learning system. From the results, it could be concluded that the new system contributed in terms of the speed of performing the final exam and high academic success. © 2020 by the authors.Article Temperature Control of an Electrical Heater by Using Fuzzy Logic(2011) Aliew,F.This project will be done in collaboration with Friedrich Schultze Company, Siegen, Germany. The aim of the project was to develop the intelligent switcher for industrial heaters to detect the interfacing object placed on a ribbed radiator and to fulfil the standard EN60335-2-30. The focal point of this work contained an intelligent algorithm and basic electronic design for sensing temperature inorder to ensure safe working of an electric heater. The fuzzy logic technique will be used to develop the intelligent "switch off" algorithm. The tests were performed by different types of heaters.Conference Object Fuzzy Semantic Web Architecture for Activity Detection in Wireless Multimedia Sensor Network Applications(Atlantis Press, 2019) Ozdin, Ali Nail; Yazici, Adnan; Koyuncu, Murat; Information Systems EngineeringThis study aims to increase the reliability of activity detection in Wireless Multimedia Sensor Networks (WMSNs) by using Semantic Web technologies extended with fuzzy logic. The proposed approach consists of three layers: the sensor layer, the data layer, and the Semantic Web layer. The sensor layer comprises a WMSN comprising sensor nodes with multimedia and scalar sensors. The data layer retrieves and stores data from the sink of WMSN. At the top of the architecture, there is a semantic web layer that includes a semantic web application server, a fuzzy reasoning engine, and a semantic knowledge base. When a new entity is detected at the sensor layer, the associated data produced by the sensors and the sink are collected in the data layer and transmitted to the semantic web application server where the data is converted into subjects, predicates, and objects, according to the ontology conceived and recorded in RDF format. Then, the fuzzy reasoning engine is automatically activated and fuzzy rules are executed to determine if there is an activity in the monitored area. Our implementation confirms that extended semantic Web technologies with fuzzy logic can have a significant impact on the detection of activities in WMSNs.Conference Object Citation - WoS: 4Citation - Scopus: 3Using Artificial Intelligence Methods to Predict Student Academic Achievement(Springer international Publishing Ag, 2022) Al-Khafaji, Mustafa; Eryilmaz, MeltemThis study applies two artificial intelligence methods represented by both the neural network and fuzzy logic to predict student achievement in the exam. The dataset used in this study was taken from an Iraqi engineering college and it represents data of 200 students who have enrolled in the computer science course. Gender, age, resources downloaded, videos viewed, discussion chat joined, exam scores used as the data set. The type of artificial neural network used was pattern neural network. Levenberg-Marquardt's algorithm was used to train the neural networks. On the other hand Sugeno fuzzy inference system was used for the fuzzy logic. The study results showed that the students who spend more time on the learning system have the most success rate. According to the results the neural network accuracy rate 73% and the fuzzy was 88%. This high accuracy rates support that artificial intelligence methods can be used to predict student academic achievement.
