Efendi Nasibov

Verified

Efendi verified their affiliation via an institutional email.

Learn more

Verified

Efendi verified their affiliation via an institutional email.

Learn more

• PhD, Dr.Sc.
• Full professor at Dokuz Eylül University

In the manufacturing area, predicting future income is more important to keep maintain their industry profits. In addition to this, most of the manufacturing company having a bit problem in predicting their manufacturing income, especially in terms of data and method used. Hence, this paper proposed another improvise method of fuzzy regression appr...

Breast cancer is the most popular malignancy among Malaysian women. In Malaysia, approximately one in every 19 women is at risk. Breast cancer is the most common cancer among Malaysian women (32.9%), followed by colorectal (11.9%) and ovarian cancers (7.2%). Many cases are found to be advanced, with considerable tumour development or metastasis to...

This study presents an innovative Visual-Inertial Odometry (VIO) approach for Unmanned Aerial Vehicles (UAVs). The proposed system integrates the modern deep learning-based SuperGlue algorithm with an information based adaptive Extended Kalman Filter (EKF). The system establishes a dynamic confidence estimation mechanism using image entropy, intens...

In recent years, studies on smart cities have attracted much attention in the literature. In the smart city concept, urban public transportation network studies are one of the most important issues. Afterthe 2000s, smart cards have been widely used in city public transportation systems. Using the data collected through the smart card, many models h...

Konut ve kiralama piyasası ülke ekonomilerinde önemli bir ekonomik yere sahiptir. Konut fiyatları genel olarak evin alanı, oda sayısı, bulunduğu kat gibi özelliklere göre belirlenmektedir. Ancak evin bu özelliklerinin yanı sıra konumu da evin pazarlama değerlendirmesi üzerinde önemli bir etkiye sahiptir. Bu bakımdan subjektif fiyat spekülasyonların...

A novel dynamic rectangular packing model for a resource allocation problem, which has many applications in Logistics Internet-of-Things (L-IoT) is considered in this study. We use an optimization approach to deal with an IoT-based problem, whose objective is to maximize the profit obtained from packing the data demand over a sequence of time frame...

Culling newly hatched male chicks in industrial hatcheries poses a serious ethical problem. Both laying and broiler breeders need males, but it is a problem because they are produced more than needed. Being able to determine the sex of chicks in the egg at the beginning or early stage of incubation can eliminate ethical problems as well as many add...

Culling newly hatched male chicks in industrial hatcheries poses a serious ethical problem. Both laying and broiler breeders need males, but it is a problem because they are produced more than needed. Being able to determine the sex of chicks in the egg at the beginning or early stage of incubation can eliminate ethical problems as well as many add...

The Gradient Boosting Regression model is a successful model used in machine learning. In this study, the FuzzyGBR algorithm, which is the novel expansion of the GBR algorithm, in case the target variable contains triangular fuzzy numbers, is discussed and its software developed in Python 3 is explained. Mathematical background required for calcula...

Gradient Boosting Regression (GBR) models are widely used and can give effective results in regression and classification problems. The main value of the approach proposed in this study is that it allows the GBR algorithm to be used even if the target variables are fuzzy. The defuzzification strategy affects the solutions found. The solutions of th...

Most of the accidents are caused by human error at sea so, decision making process made by navigators should be more computerised and automated. The supported decision making can be a step forward to decrease the risk of collision. This paper, in this respect, aims to present a deterministic approach to support optimum collision avoidance trajector...

The development of soft computing techniques in recent years has encouraged researchers to study on the path planning problem in ship collision avoidance. These techniques have widely been implemented in marine industry and technology-oriented novel solutions have been introduced. Various models, methods and techniques have been proposed to solve t...

Clustering is a commonly used tool for data management and analysis. One of the prominent group of clustering methods consists of the density-based clustering algorithms. The use of fuzzy neighborhood functions for density-based clustering algorithms are known to significantly improve the robustness, such that choosing neighborhood parameters is ra...

Currency exchange rate is one of the external factors that will affect the financial status of Malaysia. Therefore, forecasting the foreign currency exchange rate is important for the financial decision makers, bankers, academic researchers and business practitioners. Time series method is an important area of predicting future data based on the pa...

Cyberbullying has become a major problem around the world with the increasing usage of social networks. In this direction, many studies are conducted to detect cyberbullying content automatically. Most of the studies handle this problem using opinion mining approaches that focus on the text. In this study, it is aimed to present the importance of s...

Accidents are a leading cause of deaths in armed forces. The Aim of this paper is to minimize the accidents caused using weapons in the armed forces. Developing artificial intelligence technologies aim to increase efficiency more and more wherever people exist. Giving guns to inexperienced, untrained, or unpredictable mentally unhealthy people in s...

Collisions at sea are frequently caused by human-related factors, such as; manoeuvre timing mistakes, risk assessment failures and deficiencies in strategies for collision avoidance. These factors reveal the importance of the automation systems in providing safety of navigation. Thus, a decision support system was developed in this study that can b...

Ship domain is crucial for traffic risk assessment and safe navigation at sea especially in high-density traffic. This study proposes a fuzzy rule-based model to create an asymmetrical polygonal ship domain for both restricted waters and open waters. The model takes into consideration various navigational factors which are determined as a result of...

There are several ways to summarize the data set by using measures of locations, dispersions, charts, and so on. But how can the data set be represented or shown when uncertainty exists in the environment process? Usage of the fuzzy number can be a way to handle the uncertainty in the representation of the data set. This chapter focuses on the memb...

Navigators expect to feel comfortable while passing a ship and an obstacle at sea. This feeling has led to reveal the concept of ship domain. The ship domain is one of the criteria for navigational risk assessment and one of the parameters used in collision avoidance planning and traffic engineering at sea. Generally, navigators determine the domai...

Most of the accidents are caused by human error at sea so, decision making process made by navigators should be more computerised and automated. The supported decision making can be a step forward to decrease the risk of collision. This paper, in this respect, aims to present a deterministic approach to support optimum collision avoidance trajector...

The paper presents an asymmetrical polygonal fuzzy ship domain-based ship collision avoidance method considering COLREGs. The user interface is formed for practical collision avoidance decision support function via using form application developed with the C# programming language on the Microsoft Visual Studio software platform. Experimental study...

Day by day huge amounts data are produced, and evaluation of these data becomes more difficult. The data obtained should provide meaningful, correct, and accurate information. Therefore, all data must be separated into clusters correctly, and the right information from these clusters must be obtained. Having the correct clusters depends on the clus...

Belirsizliğin olduğu durumlarda bulanık sayının 0 ve 1’den farklı olarak diğer üyelik seviyelerine olanak tanıması çeşitli uygulamalarda bulanık sayının kullanılmasına yol açmıştır. Tip 1 bulanık sayılarda her bir x değerine bir üyelik seviyesi ataması yapılmaktadır. Ancak her bir x değerinin üyelik seviyesine sadece bir üyelik değeri atanmasının z...

Purpose Beside the development of technology and accessibility, ease of use, ability to reach various products and compare many products at the same time make online shopping even more popular. Despite the great advantages provided by online shopping for either consumers or retailers, there are certain issues that must be solved to improve online...

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. Çalışmanı...

Day by day huge amounts data are produced, and evaluation of these data becomes more difficult. The data obtained should provide meaningful, correct, and accurate information. Therefore, all data must be separated into clusters correctly, and the right information from these clusters must be obtained. Having the correct clusters depends on the clus...

Public transport is preferred by most of the people, since it provides various advantages. As a result, many route-planning applications are developed for users of public transport. The general aim of these applications is proposing the ideal route for a given destination; however, there are various route-planning criteria for the public transport....

Ordered weighted average (OWA) operator provides a parameterized class of mean type operators between the minimum and the maximum. It is an important tool that can reflect the strategy of a decision maker for decision‐making problems. In this study, the idea of obtaining the stress function from OWA weights has been put forward to generalize and ch...

The Fuzzy Joint Points (FJP) method is a density-based clustering method that uses a fuzzy neighborhood relation and eliminates the need for a neighborhood parameter. Even though the fuzzy neighborhood based clustering methods are proven to be fast enough, such that tens of thousands of data can be handled under a second, the space complexity is st...

Fuzzy neighborhood-based clustering algorithms overcome the parameter selection problem of classical neighborhood based clustering algorithms and offer fully unsupervised, i.e. parameter free clustering. On the other hand, due to the inherent fuzzy-calculation-overhead, they demand higher processing time and memory compared to classical clustering...

The popularity of social media applications supporting activities such as communication and sharing contents is increasing rapidly. Although social media facilitates sharing information between people, it can be used for malicious purposes. Cyberbullying, such as flaming, harassment or denigration, is one of the most important types of social media...

The paper presents a deterministic based intelligent decision making system that aims to solve the optimal collision avoidance process in the open sea. The calculation has been simulated on a web based application system developed with the "JavaScript" programming language on the "Processing" software platform. Algorithm structure of the method has...

The development of soft computing techniques in recent years has encouraged researchers to study on the path planning problem in ship collision avoidance. These techniques have widely been implemented in marine industry and technology-oriented novel solutions have been introduced. Various models, methods and techniques have been proposed to solve t...

Giderek artan uluslararası ticaret hacmine paralel olarak deniz yolu taşımacılığına olan talep artmaktadır. Dünya ticaretinin büyük çoğunluğunun deniz yolu ile gerçekleştirilmesi sebebiyle uluslararası sularda deniz trafiği yoğunluğu artmakta ve gemilerin çatışma (birbirlerine çarpması) riski olasılığının yükselmesine neden olmaktadır. Artan deniz...

In case of a collision risk between two ships, according to International Regulations for Preventing Collisions at Sea (COLREGs), the give way vessel must alter course or speed to avoid collision. In such cases ARPA (Automatic Radar Plotting Aid) can provide assistance to the operator. The radar reports that there is a potential risk of collision b...

In real life, humans communicate by means of words. Computing with words enables flexibility via fuzzy logic to reach more informative results for the classification and decision-making. Fuzzy logic handles the imprecise information. In our paper, we propose a novel fuzzy ID3 algorithm for the classification on linguistic data set, where data can b...

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 m...

The emergence of online retailing has been one of the most significant developments in business history. Altough proportion of apparel sales in online retailing also has been shown rapid increase, there are some significant barriers to overcome for expanding this market share. It is seen in literature that there are many researchers point out that...

The emergence of online retailing has been one of the most significant developments in business history. Altough proportion of apparel sales in online retailing also has been shown rapid increase, there are some significant barriers to overcome for expanding this market share. It is seen in literature that there are many researchers point out that...

Integrating clustering algorithms with fuzzy logic typically yields more robust methods, which require little to no supervision of user. The fuzzy joint points (FJP) method is a density based fuzzy clustering approach that can achieve quality clustering. However, early versions of the method hold high computational complexity. In a recent work, the...

Online shopping over internet has become very popular nowadays because of ease of use, ability to reach various products and compare them, finding cheaper products, etc. However, especially for products under textile category, some problems in fitting in size or inappropriate product for the user may arise. This study introduces a work on an online...

Integrated utilization of new technologies such as smart phones, tablet devices, and satellite maps has entered our daily lives recently. Nevertheless, many new applications are being developed mostly based on these technologies. The optimal route planning, which makes use of the public transport network structure between any selected origin and de...

In this study, OWA (Ordered Weighted Averaging) distance based C × K-nearest neighbor algorithm (C × K-NN) is considered. In this approach, from each class, where the number of classes is C, K-nearest neighbors are taken. The distance between the new sample and its K-nearest set is determined based on the OWA operator. It is shown that by adjusting...

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 ind...

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 w...

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 m...

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 m...

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 sig...

A new OWA (Ordered Weighted Averaging) distance based CxK-nearest neighbor algorithm (CxK-NN) is proposed. In this approach, K-nearest neighbors from each of the classes are taken into account instead of the well-known K-nearest neighbor (K-NN) algorithm in which only the total number, K of neighbors are considered. Distance between the classified...

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 hi...

A new CxK nearest neighbor algorithm with a new point of view is proposed. In this algorithm K neighbors from each of the classes are taken into account instead of the well-known K neighbor algorithm in which only the total number of neighbors are considered. After experiments with well-known classification datasets, we conclude that K-NN, weighted...

The aim of this paper has twofold: i to explore the fundamental concepts and methods of neighborhood-based cluster analysis with its roots in statistics and decision theory, ii to provide a compact tool for researchers. Since DBSCAN is the first method which uses the concept of neighborhood and it has many successors, we started our discussion by e...

This research is an attempt to present a proper methodology in data modification by using analytical hierarchy process (AHP) technique and fuzzy c-mean (FCM) model. The continuous data were built from binary data using analytical hierarchy process (AHP). Whereas, the binary data were created from continuous data using fuzzy c-means (FCM) model. The...

This paper proposes a proper methodology in data modification by using AHP (analytical hierarchy process) technique and FCM (fuzzy c-mean) model in the ICU (Intensive Care Unit). The binary data were created from continuous data using FCM model, while the continuous data were constructed from binary data using AHP technique. The models used in this...

Objective: Prediction of the locations of apoptosis proteins which are divided into four locations as cytoplasmic proteins, plasma membrane-bound proteins, mitochondrial inner-outer proteins and other proteins; that have different biological function in each location. Methods: In this paper, we have encoded protein sequences as amino acid compositi...

The fuzzy c-regression models (FCRM) have been known to be used in order to fit models with a certain type of mixed data. In this study, we proposed new optimal FCRM models (OFCRM). In order to obtain the least mean square error (MSE), we proposed modification of wi(x), the backward elimination method and the adjustment of the fuzzifier (w). The wi...

The linkage methods are mostly used in hierarchical clustering. In this paper, we integrate Ordered Weighted Averaging (OWA) operator with hierarchical clustering in order to find distances between clusters. In case of using OWA operator in order to find distance between clusters, OWA acts as a generalized case of single linkage, complete linkage,...

In the current paper, time series labeling task is analyzed and some solution algorithms are presented. In these algorithms, fuzzy c-means clustering, which is one of the unsupervised learning methods, is used to obtain the labels of the time series. Then K-nearest neighborhood (KNN) rule is performed on the labels to obtain more relevant smooth in...

In the increasing globalization, the performance and competitiveness of a country is the most important sign to participate in global activity. In order to remain competitive, firms tend to merger, make license agreements or partnerships while they think foreign direct investment (FDI) as an alternative strategy. In this study, we investigate wheth...