Efendi Nasiboğlu | Dokuz Eylül University (original) (raw)

Papers by Efendi Nasiboğlu

Iranian Journal of Fuzzy Systems, 2013

The main purpose of this paper is to achieve improvement in the speed of Fuzzy Joint Points (FJP)... more The main purpose of this paper is to achieve improvement in the speed of Fuzzy Joint Points (FJP) algorithm. Since FJP approach is a basis for fuzzy neighborhood based clustering algorithms such as Noise-Robust FJP (NRFJP) and Fuzzy Neighborhood DBSCAN (FN-DBSCAN), improving FJP algorithm would an important achievement in terms of these FJP-based meth- ods. Although FJP has many advantages such as robustness, auto detection of the optimal number of clusters by using cluster validity, independency from scale, etc., it is a little bit slow. In order to eliminate this disadvantage, by im- proving the FJP algorithm, we propose a novel Modied FJP algorithm, which theoretically runs approximately n=log2 n times faster and which is less com- plex than the FJP algorithm. We evaluated the performance of the Modied FJP algorithm both analytically and experimentally.

Global Journal of Information Technology: Emerging Technologies, 2017

A recent technology which makes possible for us to interact with automated systems without using ... more A recent technology which makes possible for us to interact with automated systems without using any body part is called Brain Computer Interface (BCI). In its concrete applications, electroencephalogram (EEG) is benefited by a BCI environment for being capable of obtaining brain waves. In our study, evaluation of success rates of the predictions made by C x k - Nearest Neighborhood (Cxk-NN) Algorithm for EEG Eye State Data whose states are called “Opened Eye“ and “Closed Eye“ is applied. This EEG Eye State dataset is obtained from UCI Machine Learning Repository on the web and it is a highly-used benchmark data on this field. As there are only two classes of the signals, we test binary classification performance of our classification algorithm (Cxk –NN). Comparison of those values with the ones obtained by the other successful classification algorithms in the literature applied on the same data set also take place in our study. Cxk-NN is an instance-based classification method adva...

Applied Soft Computing, 2016

A fuzzy route planning model for public transportation network

2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2015

A fuzzy route planning model based on preference degrees of stops is proposed in this study. The ... more A fuzzy route planning model based on preference degrees of stops is proposed in this study. The proposed model might also be evaluated as an intelligent system that simulates human behavior in selecting a stop to use in transportation aim. Definitions of fuzzy stop-stop, stop-line and line-line neighborhood relations are introduced. Some criteria such as the walking distance, the count of boarding at the stop and the count of lines passed through the stop are used to determine the fuzzy preference degree of a stop.

An Overview of Neighborhood-Based Clustering Methods with Fuzzy Logic

Procedia - Social and Behavioral Sciences, 2012

In this study, we handle a real life optimization problem of a metropolitan city bus service. The... more In this study, we handle a real life optimization problem of a metropolitan city bus service. The problem's focus is the fuel consumption due to dead mileage, given the bus requirements of all route schedules. We obtain the optimal route bus-garage allocations that minimize the total distance covered in all pull-out and pull-in trips, and reach significant improvement levels with respect to the current situation. We consider the midday demand fluctuations on each route, so that some of the buses have to make extra pull-in and pull-out trips before parking at their night garages after ending their last service trips. Moreover, we develop a multicriteria model which takes into account the fuzzy levels of passenger satisfaction and parking safety combined with the previous minimization objective.

Origin-destination matrix generation using smart card data: Case study for Izmir

2012 IV International Conference "Problems of Cybernetics and Informatics" (PCI), 2012

In parallel with growing populations and the development of the cities, the traffic densities and... more In parallel with growing populations and the development of the cities, the traffic densities and respectively the need for public transportation increase. While the local authorities transport the passengers to most of the locations they want, they must also maintain a high-quality public transport system to keep passengers' satisfaction levels high. The most reliable way to conduct such a good transport planning study is to benefit from actual numerical data. The number of the studies related to public transport planning by using smart card data has increased along with the developing technology and widespread usage of electronic fare collection systems. In Izmir city, which has employed an electronic fare collection system since 1999, a fully integrated public transport system has been developed that includes bus, light rail system, metro and ferry modes. In this study, the stages of constructing an origin-destination (OD) matrix that shows the regions where passengers board and alight are evaluated, and an example OD matrix generated by using actual data is interpreted.

PROMET - Traffic&Transportation, 1970

The quality of public transportation services is one of the most important performance indicators... more The quality of public transportation services is one of the most important performance indicators of modern urban policies for both planning and implementation aspects. Therefore, along with the size of the city, the significance of appropriate cost evaluation and optimization of all related transportation activities increases as well. One of the most important cost factors for the public transport agencies is naturally the fuel consumption of the vehicles. In this study, the attention is focused on the metropolitan bus transport service. The specific aim is to minimize a significant portion of total fuel utilization that occurs due to the so called deadhead trip or dead mileage, which is defined as the idle distance covered by the vehicle between the garage and the route terminal stops without carrying any passengers. In this study, the results of four mathematical models for minimizing the total deadhead trip distance covered in city bus services of Izmir are presented. The models...

Biomedizinische Technik/Biomedical Engineering, 2010

Among various types of clustering methods, partition-based methods such as k-means and FCM are wi... more Among various types of clustering methods, partition-based methods such as k-means and FCM are widely used in the analysis of such data. However, when duration between stimuli is different, such methods are not able to provide satisfactory results because they find equal size clusters according to the fundamental running principle of these methods. In such cases, neighborhood-based clustering methods can give more satisfactory results because measurement series are separated from one another according to dramatic breaking points. In recent years, bispectral index (BIS) monitoring, which is used for monitoring the level of anesthesia, has been used in sleep studies. Sleep stages are classically scored according to the Rechtschaffen and Kales (R&K) scoring system. BIS has been shown to have a strong correlation with the R&K scoring system. In this study, fuzzy neighborhood/ density-based spatial clustering of applications with noise (FN-DBSCAN) that combines speed of the DBSCAN algorithm and robustness of the NRFJP algorithm is applied to BIS measurement series. As a result of experiments, we can conclude that, by using BIS data, the FN-DBSCAN method estimates sleep stages better than the fuzzy c-means method.

A visual processing system for fuzzy clustering

In this work, a visual-interactive processing system providing facility for experiences related t... more In this work, a visual-interactive processing system providing facility for experiences related to fuzzy clustering is presented. Certain frequent algorithms of fuzzy clustering, cluster validity and selection of initial clusters are programmed as an integrated system. It is possible to select necessary methods, assess the visual outputs in the screen, constitute data set visually, and adjust the optimal cluster number

Optimal journey planning depending on distance and passenger density parameters

2013 7th International Conference on Application of Information and Communication Technologies, 2013

Since notion of smart city and related applications have become very common recently, local gover... more Since notion of smart city and related applications have become very common recently, local governments have an urge to use computers and high technology in their public transportation systems. A typical example is planning optimal journeys for travelers depending on different parameters. In this work, a graph model and a solution method based on well-known algorithms, for planning optimal journeys depending on distance and passenger density parameters are proposed.

Beklenen Aralığa Dayanan Aralık Tip II Üssel Bulanık Sayının Aralık Tip II Parametrik Yamuk Bulanık Sayı Yakınsaması

Toplu Taşımada En Az Aktarma Kriterine Göre Seyahat Planlama İçin Matematiksel Model

Her gecen gun trafi÷e cOkan arac sayOsOnOn artmasO ve mevcut ulauOm alt yapOsOnOn ihtiyaca cevap ... more Her gecen gun trafi÷e cOkan arac sayOsOnOn artmasO ve mevcut ulauOm alt yapOsOnOn ihtiyaca cevap verememesi gibi nedenlerden dolayO toplu tauOma ile seyahat planlama geliumiu ve geliumekte olan uehirlerin gundem maddeleri arasOnda ilk sOralarda yer almaktadOr. Ozellikle alt yapOlarO cok eskilere dayanan ve mevcut yerleuik duzenleri nedeniyle alt yapOlarOnda yenilemeye gidemeyen uehirler, ulauOm planlarOnda radikal de÷iuiklikler yapmak zorunda kalmaktadOr. Bu uehirlerin eski ulauOm planlarOnda uehrin onemli noktalarO arasOnda bircok paralel otobus hattO varken uzun ve geniu araclarOn neden oldu÷u trafik sOkOuOklO÷O nedeniyle, otobusler yeni planlarda metro, vapur v.b. ulauOm enstrumanlarOna besleme yapmak amacOyla aktarma aracO olarak kullanOlmaktadOr. DolayOsOyla en az aktarma kriteri, yoneticiler icin toplu tauOma ile ulauOmO planlama auamasOnda, yolcular icin de ulauOm sistemini kullanma auamasOnda cok onemli hale gelmiutir. Bu calOumada yukarOda bahsedilen kritik oneminden dolayO...

Collaborative Filtering based Course Recommender using OWA operators

2018 International Symposium on Computers in Education (SIIE), 2018

Recommendation systems guide users to choose the most appropriate items among numerous alternativ... more Recommendation systems guide users to choose the most appropriate items among numerous alternatives based on predicting their interests. Recently, it is seen that recommendation systems have become to be widely used in educational domain, especially in course recommender applications. The objectives of these systems is facilitating course selection process of students and reducing their stresses. The current course recommendation studies generally consider the most recent grades of the courses taken by students and ignore the case of repeating the course under the pass-fail or grade replacement options. However, retaking a course is the primary parameter giving opinion about tendency of the students to the courses. In this study, we propose a novel collaborative filtering (CF) based course recommendation system considering the case of repeating a course and students’ grades in the course for each repetition. We experiment different Ordered Weighted Averaging (OWA) operators which ag...

Public transport route planning: Modified dijkstra's algorithm

2017 International Conference on Computer Science and Engineering (UBMK)

Public transport applications, which aim to propose the ideal route to end users, have commonly b... more Public transport applications, which aim to propose the ideal route to end users, have commonly been used by passengers. However, the ideal route for public transport varies depending on the preferences of users. The shortest path is preferred by most users as a primary criterion for the ideal route. According to our research, Dijkstra's Algorithm is mostly used in order to find shortest path. However, Dijkstra's Algorithm is not efficient for public transport route planning, because it ignores number of transfers and walking distances. Thus, in order to minimize these shortcomings, Dijkstra's Algorithm is modified by implementing penalty system in our study. Additionally, our modified algorithm is tested on the real world transport network of Izmir and compared with the results of Dijkstra's Algorithm. It is observed that our modified algorithm is quite efficient for route planning in the public transport network in terms of the number of transfers, distance of proposed route and walking distance.

Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi

Financial difficulties make it difficult for families with disabilities to live a standard life. ... more Financial difficulties make it difficult for families with disabilities to live a standard life. In this study, a model is developed to estimate the required financial support for the families with disabilities that ensures them to have lives like the families with non-disabilities by considering main consumption groups. Hence, the aim of the study is to determine the financial support for families with disabilities that need to have the same life standards as other families by taking into consideration main consumption groups. In the analyses, the Household Budget Survey (HBS) data prepared by Turkish Statistical Institute (TurkStat) are utilized. Furthermore, 101,504 households are included in the analysis. During the development of the model, the AHP method is used. Besides, a sensitivity analysis is conducted to demonstrate the stability of the proposed model. Moreover, the suggested model considers families having different individuals as well. Öz Maddi güçlükler, engelli bireye sahip ailelerin standart bir yaşam sürmelerini zorlaştırmaktadır. Bu çalışmada, temel tüketim grupları göz önünde bulundurularak engelli bireye sahip ailelerin, engelli bireye sahip olmayan aileler gibi hayatlarını sürdürebilmeleri için gerekli finansal desteği tahmin etmek üzere bir model geliştirilmiştir. Çalışmanın amacı, ana tüketim gruplarını göz önünde bulundurarak engelli bireye sahip ailelerin diğer ailelerle aynı yaşam standartlarına sahip olmaları için gereken finansal desteğin belirlenmesidir. Analizlerde, Türkiye İstatistik Kurumu (TÜİK) tarafından hazırlanan Hanehalkı Bütçe Anketi (HBA) verileri kullanılmıştır. Analizlere 101.504 hane dahil edilmiştir. Modelin geliştirilmesi sırasında AHP yöntemi kullanılmıştır. Ayrıca önerilen modelin kararlılığını göstermek için bir duyarlılık analizi yapılmıştır. Önerilen model, farklı sayıda bireye sahip aileleri de dikkate almaktadır.

Robustness of density-based clustering methods with various neighborhood relations

ABSTRACT Cluster analysis is one of the most crucial techniques in statistical data analysis. Amo... more ABSTRACT Cluster analysis is one of the most crucial techniques in statistical data analysis. Among the clustering methods, density-based methods have great importance due to their ability to recognize clusters with arbitrary shape. In this paper, robustness of the clustering methods is handled. These methods use distance-based neighborhood relations between points. In particular, DBSCAN (density-based spatial clustering of applications with noise) algorithm and FN-DBSCAN (fuzzy neighborhood DBSCAN) algorithm are analyzed. FN-DBSCAN algorithm uses fuzzy neighborhood relation whereas DBSCAN uses crisp neighborhood relation. The main characteristic of the FN-DBSCAN algorithm is that it combines the speed of the DBSCAN and robustness of the NRFJP (noise robust fuzzy joint points) algorithms. It is observed that the FN-DBSCAN algorithm is more robust than the DBSCAN algorithm to datasets with various shapes and densities.

Modification of continuous and binary ICU data in form models

Iranian journal of fuzzy systems

The main purpose of this paper is to achieve improvement in the speed of Fuzzy Joint Points (FJP)... more The main purpose of this paper is to achieve improvement in the speed of Fuzzy Joint Points (FJP) algorithm. Since FJP approach is a basis for fuzzy neighborhood based clustering algorithms such as Noise-Robust FJP (NRFJP) and Fuzzy Neighborhood DBSCAN (FN-DBSCAN), improving FJP algorithm would an important achievement in terms of these FJP-based methods. Although FJP has many advantages such as robustness, auto detection of the optimal number of clusters by using cluster validity, independency from scale, etc., it is a little bit slow. In order to eliminate this disadvantage, by improving the FJP algorithm, we propose a novel Modified FJP algorithm, which theoretically runs approximately n/ log2 n times faster and which is less complex than the FJP algorithm. We evaluated the performance of the Modified FJP algorithm both analytically and experimentally.

Performance evaluation of industrial enterprises via fuzzy inference system approach: a case study

Soft Computing, 2014

ABSTRACT The aim of this study is not only to give self-contained and methodological steps of dat... more ABSTRACT The aim of this study is not only to give self-contained and methodological steps of data mining with its areas of applications, but also to provide a compact source of reference for the researchers who want to use data mining and fuzzy inference in their area of work. We construct a fuzzy inference system to predict the profit of the major 500 industrial enterprises of Turkey. For this aim, we use most of the data mining tools. First, we use fuzzy \(c\) -means clustering algorithm and obtain the linguistic terms of the variables. Having used decision tree technique, fuzzy rules are revealed. Eventually, we compare various defuzzification strategies to obtain crisp prediction values of our fuzzy inference system. We can conclude that the prediction results of the smallest of maxima defuzzification strategy-based fuzzy inference system has circa 40 % smaller sum square error than that of classical regression model.