Journal of Intelligent & Fuzzy Systems - Volume 39, issue 5

Authors: Algin, Ramazan | Alkaya, Ali Fuat | Agaoglu, Mustafa

Article Type: Research Article

Abstract: Feature selection (FS) has become an essential task in overcoming high dimensional and complex machine learning problems. FS is a process used for reducing the size of the dataset by separating or extracting unnecessary and unrelated properties from it. This process improves the performance of classification algorithms and reduces the evaluation time by enabling the use of small sized datasets with useful features during the classification process. FS aims to gain a minimal feature subset in a problem domain while retaining the accuracy of the original data. In this study, four computational intelligence techniques, namely, migrating birds optimization (MBO), simulated …annealing (SA), differential evolution (DE) and particle swarm optimization (PSO) are implemented for the FS problem as search algorithms and compared on the 17 well-known datasets taken from UCI machine learning repository where the dimension of the tackled datasets vary from 4 to 500. This is the first time that MBO is applied for solving the FS problem. In order to judge the quality of the subsets generated by the search algorithms, two different subset evaluation methods are implemented in this study. These methods are probabilistic consistency-based FS (PCFS) and correlation-based FS (CFS). Performance comparison of the algorithms is done by using three well-known classifiers; k -nearest neighbor, naive bayes and decision tree (C4.5). As a benchmark, the accuracy values found by classifiers using the datasets with all features are used. Results of the experiments show that our MBO-based filter approach outperforms the other three approaches in terms of accuracy values. In the experiments, it is also observed that as a subset evaluator CFS outperforms PCFS and as a classifier C4.5 gets better results when compared to k -nearest neighbor and naive bayes. Show more

Keywords: Feature selection, computational intelligence, dimensionality reduction, meta-heuristics, classification algorithms, subset evaluators

DOI: 10.3233/JIFS-189090

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6205-6216, 2020

Authors: Gutiérrez, Inmaculada | Gómez, Daniel | Castro, Javier | Espínola, Rosa

Article Type: Research Article

Abstract: In this work we introduce the notion of the weighted graph associated with a fuzzy measure. Having a finite set of elements between which there exists an affinity fuzzy relation, we propose the definition of a group based on that affinity fuzzy relation between the individuals. Then, we propose an algorithm based on the Louvain’s method to deal with community detection problems with additional information independent of the graph. We also provide a particular method to solve community detection problems over extended fuzzy graphs. Finally, we test the performance of our proposal by means of some detailed computational tests calculated …in several benchmark models. Show more

Keywords: Fuzzy clustering, networks, community detection, fuzzy graph

DOI: 10.3233/JIFS-189091

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6217-6230, 2020

Authors: Ucal Sari, Irem | Sergi, Duygu | Aytore, Can

Article Type: Research Article

Abstract: Fundraising is one of the most critical issues for non-governmental organizations (NGOs) to carry out their projects. In this paper, a search engine project which aims to find additional financial sources and increase donations for NGOs is proposed. The proposed search engine project is analyzed using fuzzy cognitive maps (FCMs) to define and manage factor influences on the success of the project. FCMs are useful tools to define long term effects of important factors for a system. First casual relations of the factors are determined and then using sigmoid function for learning algorithm, the equilibrium state for the system is …obtained. It is found that the factors generating monetary values are the most important ones for the project to be successful in long term. Show more

Keywords: Fuzzy cognitive maps, fundraising, non-governmental organizations

DOI: 10.3233/JIFS-189092

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6231-6243, 2020

Authors: Labella, Álvaro | Rodríguez, Rosa M. | Martínez, Luis

Article Type: Research Article

Abstract: Uncertainty is so common in real decision situations that it has given rise to a new decision making approach so-called linguistic decision making, in which such uncertainty is modeled by using linguistic information. Many contributions have been proposed in order to solve LDM problems by following a Computing with Words (CW) approach to obtain linguistic outputs from linguistic premises by emulating the human beings’ reasoning process. Nowadays, there are several LDM models that, together with the complexity of LDM problems, make almost impossible to find a proper solution for these problems without a support tool. FLINTSTONES is a fuzzy decision …support system that facilitates the decision process in LDM problems. This software aimed to solve LDM problems by means of the 2-tuple linguistic model, whose main advantages are high interpretability and precision of the results. However, it has other drawbacks such as the modeling of linguistic information by using solely single linguistic terms or the impossibility to model the experts’ hesitancy. Recently, the Extended Comparative Linguistic Expressions with Symbolic Translation (ELICIT) linguistic representation model was introduced in order to overcome existing drawbacks in terms of interpretability and accuracy in CW processes. This model allows to model experts’ hesitancy and, at the same time, carry out precise linguistic computations and provide interpretable results, overcoming the limitations of previous LDM models. Therefore, this contribution presents an updated version of FLINTSTONES able to manage ELICIT information in LDM problems and which integrates the ELICIT CW approach. Show more

Keywords: Linguistic decision making, ELICIT information, FLINTSTONES

DOI: 10.3233/JIFS-189093

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6245-6258, 2020

Authors: Aktas, Ahmet | Aydin, Serhat | Kabak, Mehmet

Article Type: Research Article

Abstract: To cut several types of hard materials in manufacturing, Computer Numeric Control (CNC) router machines are commonly used. The tasks to be done by different machines can be performed by a single CNC router machine. Production of parts with better quality is possible at lower costs by production with CNC router machines, and these machines improve the productivity of manufacturing system. For these reasons, determination of the appropriate CNC router machine for manufacturing systems is a crucial decision. Different factors related to properties of machines are effective on the decision. Therefore, decision makers must include different effective aspects into decision …process. Under this consideration, an analytic selection procedure for CNC router machines by taking uncertain expressions of experts on the selection criteria and variable values occur over time is proposed in this study. In order to handle the modelling difficulty of uncertainty of the statements and the value changes by time, dynamic intuitionistic multi attribute decision making is used to select the best CNC router. Applicability of the proposed selection procedure is demonstrated on an application, and a comparative analysis with dynamic neutrosophic multi attribute decision making is presented. Show more

Keywords: Dynamic decision making, intuitionistic fuzzy sets, neutrosophic sets, multi attribute decision making, CNC router selection

DOI: 10.3233/JIFS-189094

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6259-6269, 2020

Authors: Atalik, Gultekin | Senturk, Sevil

Article Type: Research Article

Abstract: Since proposed by Zadeh in 1965, ordinary fuzzy sets help us to model uncertainty and developed many types such as type 2 fuzzy, intuitionistic fuzzy, hesitant fuzzy etc. Intuitionistic fuzzy sets include both membership and non-membership functions for their each element. Ranking of a number is to identify a relationship of scalar quantity between these numbers. Ranking of fuzzy numbers play an important role in modeling problems such as fuzzy decision making, fuzzy linear programming problems. In this study, a new ranking method for triangular intuitionistic fuzzy numbers is proposed. The method based on the incircle of the membership function …and non-membership function of TIFN uses lexicographical order to rank intuitionistic fuzzy numbers. Two examples are provided to illustrate the applicability of the method. Also, a comparative study is performed to demonstrate the validity of the proposed method. The results indicate that proposed method is consistent with other methods in the literature. Also, the method overcomes the problems such as numbers being very small or close to each other. Show more

Keywords: Intuitionistic fuzzy sets, triangular intuitionistic fuzzy numbers, ranking of fuzzy numbers, incircle, inradius

DOI: 10.3233/JIFS-189095

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6271-6278, 2020

Authors: Maden, Ayça | Alptekin, Emre

Article Type: Research Article

Abstract: Blockchain practices have been attracting attention in industries other than financial services, since blockchain is not only an information technology, but also an institutional technology owing to its new currency economics and distributed structures. Today, supply chains, power, and food/agriculture have emerged as promising areas in terms of their potential to incorporate blockchain technology for improving processes and reducing costs. Logistics corporations, especially, have been concentrating on developing efficiency in integrated data, fleet management, and communication issues, to achieve cost advantages. Experts from a well-known logistics company in Turkey contributed to our study by helping to assess critical factors for …successful blockchain technology implementation. Our research topic included determining whether blockchain technology is suitable for this company. Fuzzy decision-making trial and evaluation laboratory (DEMATEL) was used to determine and evaluate the critical factors to encourage blockchain technology adoption, based on the company’s requirements. For the company experts, the factors affecting the decision to adopt blockchain technology were, in order of priority: cryptocurrency, instant money transfer, privacy, real time processing, smart contract, security, authentication, transparency, immutability, traceability, distributed ledger, reduced delays, and peer-to-peer networks. Show more

Keywords: Blockchain, Fuzzy DEMATEL, supply chain, logistics

DOI: 10.3233/JIFS-189096

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6279-6291, 2020

Authors: Oztaysi, Basar | Onar, Sezi Cevik | Kahraman, Cengiz

Article Type: Research Article

Abstract: Location-Based Systems enable novel business models that can locate a person and send an action or message to him/her. One of the most commonly adopted location-based business models is location-based advertisements. Companies can send customized messages to target customers by using location-based ads. The model is promising since the conversion rate of the customers is high. On the other side, since the customers can be targeted based on their locations and interests, the price of the advertisement should be modeled a dynamic pricing model. In this study, we propose a dynamic pricing model for location-based ads by using the Spherical …Fuzzy AHP method. Show more

Keywords: Location-based advertisements, AHP scoring, spherical fuzzy sets

DOI: 10.3233/JIFS-189097

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6293-6302, 2020

Authors: Yigit, Ahmet Talha | Samak, Baris | Kaya, Tolga

Article Type: Research Article

Abstract: Sports analytics is a field that is growing in popularity and application throughout the world. One of the open problems in this field is the valuation of football players. The aim of this study is to establish a football player value assessment model using machine learning techniques to support the transfer decisions of football clubs. The proposed model is mainly based on the intrinsic features of the individual players which are provided in Football Manager simulation game. To do this, based on the individual statistics of 5316 players who are active in 11 different major leagues from Europe and South …America, different value assessment models are conducted using advanced supervised learning techniques which include ridge and lasso regressions, random forests and extreme gradient boosting. All the models have been built in R programming language. The performances of the models are compared based on their mean squared errors and their fit to the real world examples. An ensemble model with inflation is proposed as the output. Show more

Keywords: Football analytics, machine learning, ensemble learning, extreme gradient boosting, lasso regression

DOI: 10.3233/JIFS-189098

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6303-6314, 2020

Authors: Ates, Çagatay | Özdel, Süleyman | Anarim, Emin

Article Type: Research Article

Abstract: While internet technologies have been evolving day by day, threats against them have been increasing with the same pace. One of the most serious and commonly executed attack type is Distributed Denial of Service (DDoS) attacks. Despite there are many security mechanisms against this type of attack, there is still need for new solutions due to the occurred DDoS attacks worldwide. In this work, a DDoS attack detection approach based on fuzzy logic and entropy is proposed. Network is modelled as a graph and graph-based features are used for discriminating attack traffic from attack-free traffic. Fuzzy-c-means clustering is applied based …on these features in order to show the tendencies of IP addresses or port numbers to be in a same cluster or not. Based on this uncertainty, attack and attack-free traffic are modelled. In detection phase, fuzzy membership function is used. This algorithm is tested on the real data collected from Bogaziçi University network. Show more

Keywords: Graph theory, fuzzy logic, DDoS attacks, entropy, intrusion detection

DOI: 10.3233/JIFS-189099

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6315-6324, 2020