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

Authors: Yontar, Meltem | Namli, Özge Hüsniye | Yanik, Seda

Article Type: Research Article

Abstract: Customer behavior prediction is gaining more importance in the banking sector like in any other sector recently. This study aims to propose a model to predict whether credit card users will pay their debts or not. Using the proposed model, potential unpaid risks can be predicted and necessary actions can be taken in time. For the prediction of customers’ payment status of next months, we use Artificial Neural Network (ANN), Support Vector Machine (SVM), Classification and Regression Tree (CART) and C4.5, which are widely used artificial intelligence and decision tree algorithms. Our dataset includes 10713 customer’s records obtained from a …well-known bank in Taiwan. These records consist of customer information such as the amount of credit, gender, education level, marital status, age, past payment records, invoice amount and amount of credit card payments. We apply cross validation and hold-out methods to divide our dataset into two parts as training and test sets. Then we evaluate the algorithms with the proposed performance metrics. We also optimize the parameters of the algorithms to improve the performance of prediction. The results show that the model built with the CART algorithm, one of the decision tree algorithm, provides high accuracy (about 86%) to predict the customers’ payment status for next month. When the algorithm parameters are optimized, classification accuracy and performance are increased. Show more

Keywords: Credit card, machine learning, classification, parameter optimization, ANN, SVM, CART

DOI: 10.3233/JIFS-189080

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6073-6087, 2020

Authors: Castillo, Oscar | Cortés-Antonio, Prometeo | Melin, Patricia | Valdez, Fevrier

Article Type: Research Article

Abstract: This work presents a comparative analysis of Type-1 and Type-2 fuzzy controllers to drive an omnidirectional mobile robot in line-following tasks using line detection images. Image processing uses a Prewitt filter for edge detection and determines the error from the line location. The control systems are tested using four different paths from the Robotino® SIM simulator. Also, two different strategies in the design and implementation of the controllers are presented. In the first one, a PD controller scheme is extended by using a fuzzy system to have adaptive parameters P and D, additionally, Type-2 Fuzzy sets are used to …give robustness to the controller. In the second case, a Fuzzy controller is designed to compute in a direct way the control variables and it is extended to Type-2 Fuzzy controller. Finally, experimental results and comparative analysis are presented for the five control schemes by comparing the running time and the standard deviation to measure the robustness of the control systems. Show more

Keywords: Type-2 fuzzy controller, prewitt filter, line follower

DOI: 10.3233/JIFS-189081

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6089-6097, 2020

Authors: Unver, Mustafa | Erginel, Nihal

Article Type: Research Article

Abstract: Density Based Spatial Clustering of Application with Noise (DBSCAN) is one of the mostly preferred algorithm among density based clustering approaches in unsupervised machine learning, which uses epsilon neighborhood construction strategy in order to discover arbitrary shaped clusters. DBSCAN separates dense regions from low density regions and simultaneously assigns points that lie alone as outliers to unearth the hidden cluster patterns in the datasets. DBSCAN identifies dense regions by means of core point definition, detection of which are strictly dependent on input parameter definitions: ε is distance of the neighborhood or radius of hypersphere and MinPts is minimum density …constraint inside ε radius hypersphere. Contrarily to classical DBSCAN’s crisp core point definition, intuitionistic fuzzy core point definition is proposed in our preliminary work to make DBSCAN algorithm capable of detecting different patterns of density by two different combinations of input parameters, particularly is a necessity for the density varying large datasets in multidimensional feature space. In this study, preliminarily proposed DBSCAN extension is studied: IFDBSCAN. The proposed extension is tested by computational experiments on several machine learning repository real-time datasets. Results show that, IFDBSCAN is superior to classical DBSCAN with respect to external & internal performance indices such as purity index, adjusted rand index, Fowlkes-Mallows score, silhouette coefficient, Calinski-Harabasz index and with respect to clustering structure results without increasing computational time so much, along with the possibility of trying two different density patterns on the same run and trying intermediary density values for the users by manipulating α margin. Show more

Keywords: Unsupervised machine learning, clustering, DBSCAN, IFDBSCAN, clustering validation indices, intuitionistic fuzzy sets

DOI: 10.3233/JIFS-189082

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6099-6108, 2020

Authors: Abdullah, Lazim | Rahim, Siti Nuraini

Article Type: Research Article

Abstract: Recently, researchers have shown an increased interest in integrating the neutrosophic sets with multi-criteria decision making (MCDM) methods. Previous literature have suggested the integration of neutrosophic set with the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method, in which the three memberships of neutrosophic set are utilized to solve problems that are characterized by non-deterministic information. Differently from the neutrosophic DEMATEL, which directly used three independent memberships, this paper proposes bipolar neutrosophic DEMATEL (Bipolar NS-DEMATEL) of which the positive and negative of truth, indeterminate and false memberships of bipolar neutrosophic set are introduced to enhance decision in urban sustainable development. Three …criteria and fifteen sub-criteria of urban sustainable development are the main MCDM structures that need to be solved using the proposed method. A group of experts were invited to provide rating of performance values of sub-criteria of urban sustainable development problem using a bipolar neutrosophic linguistic scale. The proposed Bipolar NS-DEMATEL is applied to segregate the sub-criteria of urban sustainable development into cause and effect groups. In addition, the network relation map is drawn to observe the interaction among the sub-criteria. The Bipolar NS-DEMATEL suggests that air quality (SC12 ) is the most important sub-criteria in managing urban sustainable development. The result also unveils that the sub-criterion safety (SC21 ) is impacted and influenced by other sub-criteria. The identification of sub-criteria in accordance with their net causer and net receiver would help the authority in prioritizing sub-criteria that may directly be affected by urban development. Show more

Keywords: Neutrosophic sets, bipolar neutrosophic sets, DEMATEL method, decision making, urban sustainable development

DOI: 10.3233/JIFS-189083

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6109-6119, 2020

Authors: Senvar, Ozlem | Akburak, Dilek | Yel, Necla

Article Type: Research Article

Abstract: Firms need to integrate multiple business functions in order to acquire, analyze, model, and evaluate information necessary for better understanding customer behaviors and making data-driven decisions to enhance the customer experience journey. This study proposes a customer oriented intelligent decision support system (IDSS) to ultimately improve the customer experience journey. Besides, a real application study is handled for a multinational company located in Turkey, considering its abrasives product sales for years of 2017 and 2018. For the data utilized in application study, the proposed methodology is constructed for customer segmentation to develop appropriate data-driven marketing strategies for customers with similar …values, preferences and other factors for creating customer-centric organizations. In this regard; firstly two-phased clustering process, which involves the hierarchical multivariate average linkage clustering algorithm and partitional k-means clustering algorithm, is used to present the number of clusters on the basis of three variables (expenditure, transaction and unit cost) and then to assign the customers to the related clusters (VIP, Platinum, Gold and Bronze), respectively. Secondly, the performances of company’s departments are ranked according to the preferences of customers from each segment considering 4Ps marketing mix concept via integrated methodology of interval type-2 Fuzzy AHP and hesitant fuzzy TOPSIS. Show more

Keywords: Intelligent decision support system (IDSS), customer experience journey, clustering, fuzzy multi criteria decision making (MCDM), interval type-2 fuzzy AHP, hesitant fuzzy TOPSIS

DOI: 10.3233/JIFS-189084

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6121-6143, 2020

Authors: Vatankhah, Ramin | Ghanatian, Mohammad

Article Type: Research Article

Abstract: There would always be some unknown geometric, inertial or any other kinds of parameters in governing differential equations of dynamic systems. These parameters are needed to be numerically specified in order to make these dynamic equations usable for dynamic and control analysis. In this study, two powerful techniques in the field of Artificial Intelligence (AI), namely Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are utilized to explain how unknown parameters in differential equations of dynamic systems can be identified. The data required for training and testing the ANN and the ANFIS are obtained by solving the direct …problem i.e. solving the dynamic equations with different known parameters and input stimulations. The governing ordinary differential equations of the system is numerically solved and the output values in different time steps are obtained. The output values of the system and their derivatives, the time and the inputs are given to the ANN and the ANFIS as their inputs and the unknown parameters in the dynamic equations are estimated as the outputs. Finally, the performances of the ANN and the ANFIS for identifying parameters of the system are compared based on the test data Percent Root Mean Square Error (% RMSE) values. Show more

Keywords: System identification, parameter identification, artificial neural network, ANFIS

DOI: 10.3233/JIFS-189085

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6145-6155, 2020

Authors: Öztürk, Melike | Alabaş-Uslu, Çiğdem

Article Type: Research Article

Abstract: Metaheuristics gained world-wide popularity and researchers have been studying them vigorously in the last two decades. A relatively less explored approach in the improvement of metaheuristics is to design new neighbor generation mechanisms. Neighbor generation mechanisms are very important in the success of any single solution-based heuristic since they directly guide the search. In this study, a neighbor generation mechanism called cantor-set based (CB) method for single solution-based heuristics which use permutation solution representation is described. The inspiration for CB method stems from the recursive algorithm that constructs a cantor set which is a fractal set. Three variations of CB …method are discussed (CB-1, CB-2, CB-3) considering the presented design possibilities. The computational experiments are conducted by embedding the mechanisms into the classical local search and simulated annealing algorithms, separately, to test their efficiency and effectiveness by comparing them to classical swap and insertion mechanisms. The traveling salesman problem (TSP) and quadratic assignment problem (QAP) which are very different problems that have incompatible characteristics have been chosen to test the mechanisms and sets of benchmark instances with varying sizes are chosen for the comparisons. The computational tests show that CB-2 gives very favorable results for TSP and CB-1 gives favorable results for QAP which means that CB-2 is suitable for problems that have steep landscapes and CB-1 is suitable for the problems that have flat landscapes. It is observed that CB-3 is a more generalized mechanism because it gives consistently good results for both TSP and QAP instances. The best mechanism for a given instance of the both problem types outperforms the classical neighbor generation of swap and insertion in terms of effectiveness. Show more

Keywords: Neighbor generation, local search, simulated annealing, cantor set, traveling salesman problem, quadratic assignment problem

DOI: 10.3233/JIFS-189086

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6157-6168, 2020

Authors: Valdez, Fevrier | Castillo, Oscar | Cortes-Antonio, Prometeo | Melin, Patricia

Article Type: Research Article

Abstract: In this paper, we are presenting a survey of research works dealing with Type-2 fuzzy logic controllers designed using optimization algorithms inspired on natural phenomena. Also, in this review, we analyze the most popular optimization methods used to find the important parameters on Type-1 and Type-2 fuzzy logic controllers to improve on previously obtained results. To this end have included a summary of the results obtained from the web of science database to observe the recent trend of using optimization methods in the area of optimal type-2 fuzzy logic control design. Also, we have made a comparison among countries of …the network of researchers using optimization methods to analyze the distribution and impact of the papers. Show more

Keywords: Nature inspired optimization, Type-2 fuzzy logic, fuzzy control

DOI: 10.3233/JIFS-189087

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6169-6179, 2020

Authors: Tüysüz, Nurdan | Kahraman, Cengiz

Article Type: Research Article

Abstract: This study presents a multi-experts multiple criteria decision making approach for quantitatively evaluating social sustainable development factors. The proposed model which integrates Z-fuzzy numbers and fuzzy AHP enables to weight and rank social sustainable development factors, which may give guidance to many sustainable development researches. In addition to the first usage of the Z-fuzzy numbers for the weighting decision of social sustainable development factors, another contribution of the study is presenting the Z-fuzzy numbers integrated AHP method with multi-experts which can be useful in many problems and applications containing uncertainty. The most important advantage of the Z-fuzzy numbers integrated AHP …method is that it allows the degree of confidence of decision makers to be included to the calculations. An application of the proposed approach is also presented for prioritizing the social sustainable development factors based on the experts’ evaluations together with a sensitivity analysis. Show more

Keywords: AHP, group decision making, z-number, sustainability, multicriteria

DOI: 10.3233/JIFS-189088

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6181-6192, 2020

Authors: Otay, Irem | Jaller, Miguel

Article Type: Research Article

Abstract: This paper proposes an Integrated Fuzzy Analytic Hierarchy Process (AHP) with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method using Pythagorean fuzzy sets for the wind farm location selection problem. The method combines the advantages of the two methodologies to consider uncertainties and lack of information in the decision-making process (human expert capacities) and enables better representation of membership and non-membership functions, and at the same time, allows for the evaluation of large numbers of alternatives and criteria. The authors implement the method to evaluate four potential sites near cities located in the west and north-west …regions of Turkey, using seven main criteria and twenty-five sub-criteria. The analyses are based on the judgements of three experts/decision-makers. Moreover, the authors compare the results (site ranking) of the methodology, with those from a Pythagorean Fuzzy AHP and an interval-valued Type-2 fuzzy AHP method. With the additional consideration of the sub-criteria, the proposed method generates slight differences in the ranking compared to the previously evaluated methods. Show more

Keywords: Wind energy, location selection, Pythagorean fuzzy AHP, Pythagorean fuzzy TOPSIS, interval-valued Pythagorean fuzzy sets

DOI: 10.3233/JIFS-189089

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6193-6204, 2020

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

Authors: Tolga, A. Cagri | Basar, Murat

Article Type: Research Article

Abstract: Increasing population in the world drives people to find a different type of feeding regime. Even if there is an immense augmentation in crowd brilliant innovators are looking for new ways of farming more efficiently. Hydroponics is one of the novel paths that is a planting system without soil. The system reduces water usage by 95% and with the same rate provides efficiency in the crop, furthermore, sustainability is highly supplied. Traditional smart farming applied in the rural area strains immense transportation and brokership costs. In these days innovators make smart agriculture in vessel containers. Especially vertical and smart farming …made in the suburban area of the cities offers new opportunities on vegetables’ abundance. In this paper, the efficiency of this offered system is examined with minimizing the investment cost data. The system itself and the investment area have abounded with myriad uncertainties. Fuzzy logic tackles with those vaguenesses and fuzzy Evaluation Based on Distance from Average Solution (EDAS) method supplies assistance in the decision-making process of system evaluation. In addition, TODIM (a risk sensitive iterative multi-criteria decision making method based on Prospect Theory) is employed to check the evaluation of those three alternatives and to monitor how risk perception affects decision processes. A micro-based application is performed and attractive results are achieved. Show more

Keywords: Vertical urban agriculture, fuzzy EDAS method, fuzzy TODIM, investment cost, smart farming

DOI: 10.3233/JIFS-189100

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6325-6337, 2020

Authors: Çakır, Esra | Ulukan, Ziya

Article Type: Research Article

Abstract: Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power …plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem. Show more

Keywords: Project management, nearest interval approximation method, goal programming, fuzzy multi-objective linear programming, nuclear power plant

DOI: 10.3233/JIFS-189101

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6339-6350, 2020

Authors: Alcalde, Cristina | Burusco, Ana

Article Type: Research Article

Abstract: Information extracted from L-fuzzy contexts is substantially improved by taking into account different points of view, which can roughly be represented by criteria. This work addresses the general study of L-fuzzy contexts were a set of criteria is introduced, analyzing situations in which their evolution over time is known. The relationship among criteria is also an important point in the study. In this sense, the treatment will vary depending on whether they are independent criteria or there exists dependency among them. Of special importance will be those elements that stand out for presenting a positive temporal evolution. Four algorithms are …proposed in order to analyze the different situations. Finally, the applicability of the results is shown thought an example where the opinion of the clients of several hotels is analyzed taking into account both the type of traveler considered and the different aspects of the establishments on which a score is given. Show more

Keywords: L-fuzzy concept analysis, L-fuzzy context sequences, L-fuzzy contexts associated with criteria, WOWA operators, Choquet integrals

DOI: 10.3233/JIFS-189102

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6351-6362, 2020

Authors: Büyüközkan, Gülçin | Mukul, Esin

Article Type: Research Article

Abstract: Smart health applications are raising a growing interest around the world thanks to its potential to act proactively and solve health related problems with smart technologies. Smart health technologies can provide effective healthcare services such as personalization of treatments through big data, robotics in cure and care, artificial intelligence support to doctors, etc. The mixed structure of the evaluation of smart health technologies involves various contradictory criteria. However, when information is of uncertain nature, it is difficult to decide on how to treat. A hesitant fuzzy linguistic term set (HFLTS) approach is applied to overcome such uncertainties related to this …multi-criteria decision-making (MCDM) problem. This approach can be used to facilitate experts’ decision-making processes in complex and uncertain situations. In this study, an integrated hesitant fuzzy linguistic (HFL) MCDM approach is proposed to evaluate smart health technologies. The criteria are weighted with HFL Analytic Hierarchy Process (AHP), and then, smart health technologies are evaluated with the HFL Combinative Distance-based Assessment (CODAS) method. A comparative analysis with HFL COPRAS and HFL TOPSIS is applied. Lastly, the potential of this approach is presented through a case study. Show more

Keywords: Hesitant fuzzy linguistic term set, multi-criteria decision making, smart health, smart health technologies

DOI: 10.3233/JIFS-189103

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6363-6375, 2020

Authors: Barbara, Gładysz | Dorota, Kuchta

Article Type: Research Article

Abstract: The paper is based on a survey analyzing the success of IT projects in Poland as function of the cooperation with different stakeholders. The project’s participants expressed their subjective opinions on the effectiveness of the collective cooperation with various stakeholder groups. The impact of cooperation with different stakeholder groups: project team, management of the project implementation unit, suppliers and end users of the final product on the success of the project is examined. To this end, intuitionistic fuzzy sets, a correlation coefficient of intuitionistic fuzzy sets and an original method of intuitionistic fuzzy regression are applied. The conclusions point to …the most important stakeholder groups for the complete success and for the avoidance of a complete failure of IT projects. Some possibilities of the extension of the proposed method are indicated, so that the decision maker can adopt it to his or her preferences in searching for project success or failure factors. Show more

Keywords: IT Project Management, IT project success, project stakeholder, intuitionistic fuzzy set, intuitionistic correlation, intuitionistic regression

DOI: 10.3233/JIFS-189104

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6377-6389, 2020

Authors: Kalender, Zeynep Tugce | Kilic, Huseyin Selcuk | Tuzkaya, Gulfem | Dascioglu, Busra Gulnihan

Article Type: Research Article

Abstract: The prevalence of environmental studies in the academy has increased in recent years, depending on the adverse effects of global warming on natural resources. Besides various environmentally benign applications, one of the most important instruments on eliminating the negative environmental effects of an increasing population is electric vehicles. There are various topics within the concept of electric vehicles, including the determination of electric vehicle type, routing, network design, and so on. However, in this study, determining the locations of electric charging stations is the main focus. The problem is handled as a multi-criteria decision-making problem with the consideration of the …uncertainties in the decision-making environment. Specifically, the judgments of decision-makers play a critical role in the success of decisions, but for a decision-maker, it is usually difficult to express his/her preferences by using only one linguistic term due to the structure of some criteria type. Hence, with the proposed methodology, in this study, criteria are firstly classified as fuzzy and crisp according to their objective or subjective characteristics. Afterwards, besides the utilization of classic techniques for crisp type criteria, probabilistic linguistic terms sets are utilized for fuzzy type criteria with an extended version of TOPSIS. The proposed methodology is used for the comparison of 39 alternative electric charging locations in Istanbul, which is one of the most crowded cities in Europe. Show more

Keywords: Electric charging stations, plug-in electric vehicles, parking-lot-based charging location, TOPSIS, multi-criteria decision-making, probabilistic linguistic term sets

DOI: 10.3233/JIFS-189105

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6391-6406, 2020

Authors: Ilbahar, Esra | Cebi, Selcuk | Kahraman, Cengiz

Article Type: Research Article

Abstract: Effective utilization of renewable energy sources is an essential component of countries’ sustainable development strategies. A thorough evaluation of renewable energy alternatives is required to assure maximum exploitation of resources. The evaluation of renewable energy sources is a complicated problem since many criteria, even some of them are conflicting, must be taken into account simultaneously. Pythagorean fuzzy sets are better able to reflect uncertainty and vagueness in an assessment process by providing a greater domain for decision makers to describe their opinions. Therefore, this study aims at prioritizing renewable energy alternatives by employing interval-valued Pythagorean fuzzy WASPAS method. The obtained …results are compared to the results of intuitionistic type-2 fuzzy WASPAS, interval-valued intuitionistic fuzzy WASPAS and crisp WASPAS methods. Biomass is selected to be the best renewable energy alternative for Central Anatolia Region of Turkey. Show more

Keywords: Renewable energy evaluation, Pythagorean fuzzy sets, WASPAS

DOI: 10.3233/JIFS-189106

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6407-6417, 2020

Authors: Marcek, Dusan

Article Type: Research Article

Abstract: To forecast time series data, two methodological frameworks of statistical and computational intelligence modelling are considered. The statistical methodological approach is based on the theory of invertible ARIMA (Auto-Regressive Integrated Moving Average) models with Maximum Likelihood (ML) estimating method. As a competitive tool to statistical forecasting models, we use the popular classic neural network (NN) of perceptron type. To train NN, the Back-Propagation (BP) algorithm and heuristics like genetic and micro-genetic algorithm (GA and MGA) are implemented on the large data set. A comparative analysis of selected learning methods is performed and evaluated. From performed experiments we find that the …optimal population size will likely be 20 with the lowest training time from all NN trained by the evolutionary algorithms, while the prediction accuracy level is lesser, but still acceptable by managers. Show more

Keywords: ARIMA models, neural networks, learning algorithms, time series forecasting

DOI: 10.3233/JIFS-189107

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6419-6430, 2020

Authors: Haktanır, Elif

Article Type: Research Article

Abstract: Malcolm Baldrige National Quality Award (MBNQA) is a quality assessment and rewarding system that aims to increase the awareness of quality management. Although the award is launched in the USA in 1989 and only given to the U.S based companies, it is recognized internationally. There are 7 types of categories in the award system (Leadership, Strategic planning, Customer focus, Measurement, analysis, and knowledge management, Workforce focus, Process management, and Results) where the evaluation is made over 1000 points and each category has its own weight. Since almost all the publications in the literature are based on crisp measurements and evaluations …of the system performances, we proposed a multi attribute decision making (MADM) method using interval valued Pythagorean fuzzy weighted averaging (IVPFWA) and interval valued Pythagorean fuzzy weighted geometric (IVPFWG) aggregation operators for MBNQA assessment to represent the decision makers’ subjective evaluations better. A comparison of the results with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method and an illustrative example are presented in the study. Show more

Keywords: Malcolm Baldrige National Quality Award, interval-valued Pythagorean fuzzy sets, multi attribute decision making, interval-valued Pythagorean fuzzy aggregation operators

DOI: 10.3233/JIFS-189108

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6431-6441, 2020

Authors: Piltan, Farzin | Prosvirin, Alexander E. | Kim, Jong-Myon

Article Type: Research Article

Abstract: Robotic manipulators represent a class of nonlinear and multiple-degrees-of-freedom robots that have pronounced coupling effects and can be used in various applications. The challenge of understanding complexity in a system’s dynamic behavior, coupling effects, and sources of uncertainty presents substantial challenges regarding fault estimation, detection, identification, and tolerant-control (FEDIT) in a robot manipulator. Thus, a proposed active fault-tolerant control algorithm, based on an adaptive modern sliding mode observer, is represented. Due to the effect of the system’s complexities and uncertainties for fault estimation, detection, and identification (FEDI), a sliding mode observer (SMO) is proposed. To address the sliding mode observer …drawbacks for FEDI such as high-frequency oscillation (chattering) and fault estimation accuracy, the modern (T-S fuzzy higher order) technique is represented. In addition, the adaptive technique is applied to the modern sliding mode observer (MSMO) to self-tune the coefficients of the fault estimation observer to increase the reliability and robustness of decision-making for diagnosis of the fault. Next, the residual delivered by the adaptive MSMO (AMSMO) is split into windows, and each window is characterized by a numerical parameter. Finally, the machine learning technique known as a decision tree adaptively derives the threshold values that are used for problems of fault detection and fault identification in this work. Due to control of the effective fault, a surface automated new sliding mode controller (SANSMC) is presented in this work. To address the challenge of chattering and unlimited uncertainties (faults), the AMSMO is applied to the sliding mode controller (SMC). In addition, the surface-automated technique is used to fine-tune the surface coefficient to reduce the chattering and faults in the robot manipulator. The results show that the machine learning-based automated robust hybrid observer significantly improves the robustness, reliability, and accuracy of FEDIT in unknown conditions. Show more

Keywords: Robot manipulator, sliding mode algorithm, observation technique, fuzzy logic technique, high-order sliding mode observer, adaptive technique, fault estimation, fault detection, fault identification, fault-tolerant control.

DOI: 10.3233/JIFS-189109

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6443-6463, 2020

Authors: Ercan-Teksen, Hatice | Anagün, Ahmet Sermet

Article Type: Research Article

Abstract: Control chart is one of the statistical methods to analyze the process. The use of fuzzy sets in control charts, which are divided into qualitative and quantitative data, has been applied in many studies recently. Especially for qualitative control charts, data collection is more difficult and more subjective. Therefore, fuzzy sets are used to reduce losses in data. There are many control chart studies created by type-1 fuzzy sets available in the literature. In recent years, examples of fuzzy control charts with extensions of fuzzy sets have been found. The aim of this study is to obtain c-control chart for …intuitionistic fuzzy sets. For this purpose, defuzzification and likelihood methods are used. In particular, with the application of the likelihood method to intuitionistic fuzzy control charts, this will be considered as a pioneering study in the literature. In addition, a novel likelihood method was developed for intuitionistic fuzzy sets and used here to provide flexibility. Show more

Keywords: Intuitionistic fuzzy sets, fuzzy control charts, intuitionistic fuzzy comparison methods

DOI: 10.3233/JIFS-189110

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6465-6473, 2020

Authors: Karadayi-Usta, Saliha | Bozdag, Cafer Erhan

Article Type: Research Article

Abstract: Medical tourism service offers a professional healthcare opportunity by travelling abroad with the chance of touristic and cultural activities at the destination country. Medical travelers prefer a foreign country for treatment due to long waiting periods, high costs, excessive number of patients, inadequate number of healthcare professionals and inadequate cutting-edge technological equipment at their country of residence. An assistance company (AC) is a legal requirement to support medical tourists in Turkey during the treatment period, and offers alternative healthcare service providers (HSPs) that are public hospitals, private hospitals and private clinics at the first phase of the medical tourism service. …Moreover, there are specific HSPs certificated by the government, and a few number of public hospitals authenticated for medical tourism. By taking the whole above statements into consideration, HSP selection is a key decision-making point differentiating from a traditional hospital selection of a patient. Medical tourists must evaluate various criteria in order to select a proper HSP. Additionally, these decision criteria are often vague, complex, indeterminate and inconsistent information in the HSP type decision. Hence, in this study, a decision making model based on neutrosophic fuzzy sets considering HSP selection in every aspect (truthiness, indeterminacy and falsity) is suggested. Show more

Keywords: Neutrosophic fuzzy sets, decision making, medical tourists, healthcare service provider type selection

DOI: 10.3233/JIFS-189111

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6475-6485, 2020

Authors: Kalaycı, Tolga Ahmet | Asan, Umut

Article Type: Research Article

Abstract: A frequently encountered case in developing a classification model is the presence of embedded clusters, formed by data used for training. A good example for this case may be the differences in purchasing styles of e-commerce customers in a purchase propensity modelling problem. While some customers prefer a detailed research about prices, functionalities and comments, some others may need a shorter examination to make a purchase decision. Although feeding such cluster information into the classification model has been shown by recent studies to improve the prediction performance, this valuable information has been largely ignored in classical modeling techniques in general …and neural networks in particular. This paper proposes a feedforward neural network regularization method which incorporates cluster information into networks’hidden nodes. Within the forward propagation and backpropagation calculations of the network, a non-randomized matrix is used to assign hidden nodes to different observation clusters. This matrix manipulates the activation value of a hidden node for each observation in line with the observation’s membership degree to the cluster that the node is assigned to. Also, through the alternating use of randomized binary and non-randomized matrices within iterations, the proposed method successfully fulfills the regularization task. Experiments were performed for different settings and network architectures. Empirical results demonstrate that the proposed method works well in practice and performs statistically significantly better than existing alternatives. Show more

Keywords: Neural networks, fuzzy clustering, classification, regularization, machine learning

DOI: 10.3233/JIFS-189112

Citation: Journal of Intelligent &Fuzzy Systems, vol. 39, no. 5, pp. 6487-6496, 2020

Authors: Goker, Nazli | Dursun, Mehtap | Albayrak, Esra

Article Type: Research Article

Abstract: Supply chain agility is an indispensable way for the companies to quickly response to the demands of the customers. For this reason, agility of supply chain is indispensable in dynamic markets that have high scale of diversity and subjective needs. Supply chain agility needs a systemic procedure that gives priority to feedbacks of customers and follows the changes of competitors in the sector. An efficient supplier evaluation procedure is indispensable for reaching supply chain agility. Agile supplier selection needs to take into account various criteria that incorporate vagueness and uncertainty, obtaining general a multiple level hierarchical system that allows conducting …a more efficient decision analysis. Thus, in this paper an integrated fuzzy multi-criteria group decision making procedure based on quantifier-guided ordered weighted average (OWA) method and fuzzy integral, which allows incorporating uncertain data expressed as linguistic terms into the analysis, is proposed for identifying the most suitable agile supplier alternative. In group decision making issues, aggregating experts’opinions is vital to achieve more robust results. As quantifier-guided OWA method is appropriate for decision making problems under uncertain environments, it is employed for the aggregation of experts’evaluations. The developed decision procedure is illustrated via a case study performed in a dye producer in Turkish dye sector. Show more

Keywords: Imprecise data, agile supplier selection, fuzzy measure, quantifier-guided OWA, fuzzy integral

DOI: 10.3233/JIFS-189113

Citation: Journal of Intelligent &Fuzzy Systems, vol. 39, no. 5, pp. 6497-6505, 2020

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

Article Type: Research Article

Abstract: Pythagorean fuzzy sets (PFS) are an extension of intuitionistic fuzzy sets introduced by Atanassov [1 ]. PFSs have the advantage of providing larger domains for assigning membership and non-membership degrees satisfying that their squared sum is at most equal to one. PFS have been often used in modeling the problems under vagueness and impreciseness in order to better define the problems together with the hesitancy of decision makers. Different human emotions and behaviors can be modeled in humanoid robots (HR) by fuzzy sets. In this paper, facial expressions of a humanoid robot are modeled depending on the degrees of the …emotions. Larger degree of emotion causes a stronger indicator of the facial mimic. Show more

Keywords: Fuzzy sets, extensions, intuitionistic fuzzy sets, Pythagorean fuzzy sets, picture fuzzy sets, q-rung orthopair fuzzy sets, spherical fuzzy sets

DOI: 10.3233/JIFS-189114

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6507-6515, 2020

Authors: Caglayan, Nadide | Satoglu, Sule Itir | Kapukaya, E. Nisa

Article Type: Research Article

Abstract: Sales forecasting with high accuracy is crucial in many industries. Especially, in fast-moving consumer goods, retail and apparel industries, the products are not tailor-made and must be produced and made available in chain stores to the customers, in advance. Therefore, for sales and operations planning, forecast information is required. However, traditionally, time series based forecasting techniques are used that merely consider the seasonality, trend, auto-regressive and cyclic factors. This type of forecasting is not suitable especially in cases where many other factors involved and affect the product sales. In apparel retail industry, special factors such as promotions, special days, weather …(temperature), and location of the store may affect the product demands of the chain stores. The unique aspect of this study is that the sales of a product family of the fashion retail chain stores were estimated by means of artificial neural networks, for the first time in the literature. Besides, in this study, new significant factors in forecasting were explored that influence the demand of the chain stores. So, in this study, artificial neural networks are developed and used for sales forecasting of a product family of a real chain store, in Turkey. The stores exist in many cities, and some of the cities have much more stores than the other cities. The city with the highest number of stores was selected and some of the stores in this city chosen among them. The past sales, sales price and promotion data of selected stores are used. In addition, store information, number of customers visiting the store, and weather temperature data are included in the model. Sales are estimated by artificial neural networks. Besides, Regression Analysis was used for forecasting and the results of both techniques were compared. As a result of the study, the most appropriate network structure has been obtained, and a high sales forecasting performance has been reached. Show more

Keywords: Artificial neural networks, data analysis, demand forecasting, retail sectors

DOI: 10.3233/JIFS-189115

Citation: Journal of Intelligent &Fuzzy Systems, vol. 39, no. 5, pp. 6517-6528, 2020

Authors: Dogan, Onur | Oztaysi, Basar

Article Type: Research Article

Abstract: Customer-based practices enable benefits to organizations in a contentious business. Offering individualized proposals increase customer loyalty to be able to afloat. Understanding customers is a vital difficulty to perform personalized recommendations. As a demographic feature, gender information essentially cannot be captured by human tracking technologies. Hence, several procedures are improved to predict undiscovered gender information. In the research, the followed indoor paths in a shopping mall are used to predict customer genders using fuzzy c-medoids, one of the soft clustering techniques. A Levenshtein-based fuzzy classification methodology is proposed the followed paths as string data. Although some studies focused on gender …prediction, no research has centered on path-oriented. The novelty of the investigation is to analyze customer path data for the gender classes. Show more

Keywords: Gender prediction, string classification, soft clustering, path classification, levenshtein, fuzzy c-medoids

DOI: 10.3233/JIFS-189116

Citation: Journal of Intelligent &Fuzzy Systems, vol. 39, no. 5, pp. 6529-6538, 2020

Authors: Ömerali, Mete | Kaya, Tolga

Article Type: Research Article

Abstract: Since decades managers and scientists have been investigating the vertical boundaries of the firms to understand when to buy goods and services or make them internally. Since there are number of pros and cons on making or buying, the decision is very complex. Firms not only focus on the tangible terms like transaction costs and economies of scale but also consider other factors like information asymmetry, know-how protection and data source quality to keep or gain competitive advantage. Yet this isn’t simple enough, with the rapid growth of technology, the fourth industry revolution and digitalization challenge firms even further. Deciding …on digitalization strategy isn’t anywhere different than the existing make buy decision that firms have faced in the past, however this time with an increased complexity. In this article, we are aiming to understand what strategies firms should apply during their journey in industry 4.0 and a verification with an industrial case study. The purpose of this study is to suggest a Type-2 Fuzzy COPRAS methodology to aid the buy or implement decisions of firms in IOT domain. Show more

Keywords: Internet of Things, Type-2 Fuzzy COPRAS, Digitalization, Industry 4.0, Make or Buy

DOI: 10.3233/JIFS-189117

Citation: Journal of Intelligent &Fuzzy Systems, vol. 39, no. 5, pp. 6539-6552, 2020

Authors: Bolturk, Eda | Gülbay, Murat | Kahraman, Cengiz

Article Type: Research Article

Abstract: Sustainable energy selection has been a very popular problem among the researchers and various models including deterministic, probabilistic and fuzzy approaches have been developed for the solution of this problem. Fuzzy approaches to sustainable energy selection problems have been often handled in the literature. Aggregation operators for multi-expert decision making problems are an alternative solution technique for multi criteria decision making problems. Since neutrosophic and intuitionistic fuzzy aggregation operators are comparable extensions of ordinary fuzzy sets, they have been employed to aggregate multi-expert judgments. An illustrative energy selection problem is presented, solved by two approaches, and results are compared. The …same linguistic data have been used for the comparison purpose. Show more

Keywords: Fuzzy aggregation operator, multi-attribute decision making, intuitionistic fuzzy set, neutrosophic fuzzy sets, sustainable energy selection

DOI: 10.3233/JIFS-189118

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6553-6563, 2020

Authors: Jahanandish, Roya | Khosravifard, Amir | Vatankhah, Ramin

Article Type: Research Article

Abstract: This paper proposes a new method to improve fuzzy control performance accuracy in the stabilization of the two-axis gimbal system. To this end, due to the fact that the knowledge of the accurate behavior of the system plays a substantial role in fuzzy control performance, all the uncertain parameters of the dynamic model such as friction, mass imbalance and moments of inertia are estimated prior to the controller design and without imposing any computational burden on the control scheme. To estimate the uncertainties and disturbances which exist in the dynamic equations, an identification process formulated as an inverse problem is …utilized, and the Gauss– Newton method is adopted for the optimization process. Regarding the severe sensitivity of inverse problems to measurement errors, this undesirable effect is reduced by using a proper smoothing technique. In order to increase the accuracy of the final results, a novel procedure for calculation of the sensitivity coefficients of the inverse problem is proposed. This procedure is based on the direct differentiation of the governing equations with respect to the unknown parameters. At the end, simulation results are presented to confirm the effectiveness of the proposed scheme. Show more

Keywords: Fuzzy control, parameter estimation, two-axis gimbal

DOI: 10.3233/JIFS-189119

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6565-6577, 2020

Authors: Çağlıyor, Sandy | Öztayşi, Başar | Sezgin, Selime

Article Type: Research Article

Abstract: The motion picture industry is one of the largest industries worldwide and has significant importance in the global economy. Considering the high stakes and high risks in the industry, forecast models and decision support systems are gaining importance. Several attempts have been made to estimate the theatrical performance of a movie before or at the early stages of its release. Nevertheless, these models are mostly used for predicting domestic performances and the industry still struggles to predict box office performances in overseas markets. In this study, the aim is to design a forecast model using different machine learning algorithms to …estimate the theatrical success of US movies in Turkey. From various sources, a dataset of 1559 movies is constructed. Firstly, independent variables are grouped as pre-release, distributor type, and international distribution based on their characteristic. The number of attendances is discretized into three classes. Four popular machine learning algorithms, artificial neural networks, decision tree regression and gradient boosting tree and random forest are employed, and the impact of each group is observed by compared by the performance models. Then the number of target classes is increased into five and eight and results are compared with the previously developed models in the literature. Show more

Keywords: Machine learning algorithms, motion picture industry, forecasting

DOI: 10.3233/JIFS-189120

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6579-6590, 2020

Authors: Haktanır, Elif | Kahraman, Cengiz

Article Type: Research Article

Abstract: Failure mode and effects analysis (FMEA) is a structured approach for discovering possible failures that may occur in the design of a product or process. Since classical FMEA is not sufficient to represent the vagueness and impreciseness in human decisions and evaluations, many extensions of ordinary fuzzy sets such as hesitant fuzzy sets, intuitionistic fuzzy sets, Pythagorean fuzzy sets, spherical fuzzy sets, and picture fuzzy sets. Classical FMEA has been handled to capture the uncertainty through these extensions. Neutrosophic sets is a different extension from the others handling the uncertainty parameters independently. A novel interval-valued neutrosophic FMEA method is developed …in this study. The proposed method is presented in several steps with its application to an automotive company in order to prioritize the potential causes of failures during the design process by considering multi-experts’ evaluations. Show more

Keywords: Failure mode and effect analysis, interval valued neutrosophic sets, risk priority number

DOI: 10.3233/JIFS-189121

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6591-6601, 2020

Authors: Yildiz, Didem | Temur, Gul T. | Beskese, Ahmet | Bozbura, F. Tunc

Article Type: Research Article

Abstract: In contemporary business life, retention of talented employees is crucial for organizations to preserve created value. Considering their attitudes, behaviors and personality, millenials are different from former generations, and retaining them requires a distinct management approach. This study aims to provide the decision makers with a more effective and efficient tool for evaluating career management activity types leading to employee retention of millenials. A novel method, Spherical Fuzzy Analytic Hierarchy Process (SFAHP) is used in the study to; (i) define the importance levels of the criteria having impact on employee retention, and (ii) assess various career management activity types for …employee retention. To ensure the practical use of the model, a numerical example from real world is presented. The results indicate that “leadership and management” is the most important factor, and “development-oriented career management activities” is the highest impact activity type in increasing the employee retention. Show more

Keywords: Employee retention, millenials, multi criteria decision making, spherical fuzzy sets, spherical fuzzy analytic hierarchy process, talent management

DOI: 10.3233/JIFS-189122

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6603-6618, 2020

Authors: Tekin, Ahmet Tezcan | Çebi, Ferhan

Article Type: Research Article

Abstract: Within the most productive route, online travel agencies (OTAs) intend to use advanced digital media ads to expand their piece of the industry as a whole. The metasearch engine platforms are among the most consistently used digital media environments by OTAs. Most OTAs offer day by day deals in metasearch engine platforms that are paying per click for each hotel to get reservations. The administration of offering methodologies is critical along these lines to reduce costs and increase revenue for online travel agencies. In this study, we tried to predict both the number of impressions and the regular Click-Through-Rate (CTR) …level of hotel advertising for each hotel and the daily sales amount. A significant commitment of our research is to use an extended dataset generated by integrating the most informative features implemented in various related studies as the rolling average for a different amount of day and shifted values for use in the proposed test stage for CTR, impression and sales prediction. The data is created in this study by one of Turkey’s largest OTA, and we are giving OTA’s a genuine application. The results at each prediction stage show that enriching the training data with the OTA-specific additional features, which are the most insightful and sliding window techniques, improves the prediction models ’ generalization capability, and tree-based boosting algorithms carry out the greatest results on this problem. Clustering the dataset according to its specifications also improves the results of the predictions. Show more

Keywords: CTR prediction, impression prediction, sales prediction, data enrichment, clustering, fuzzy clustering

DOI: 10.3233/JIFS-189123

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6619-6627, 2020

Authors: Kılıç, Hakan | Kabak, Özgür

Article Type: Research Article

Abstract: Human development and competitiveness have a causal relation. However, the literature is not clear on which one affects the other. This study investigates the bilateral relation between human development and competitiveness. For this purpose, initially, Fuzzy Analytic Network Process (FANP) is utilized to develop a composite index based on the relative importance weights of respective human development and competitiveness drivers. By FANP, the effects of key dimensions of human development and indexes of competitiveness on each other are taken into account. Subsequently, countries’ efficiencies on converting their human development to competitiveness and inversely, competitiveness to human development is measured by …Data Envelopment Analysis (DEA). Two different DEA models are developed to consider the bilateral relations. 45 countries are evaluated using both FANP and DEA models. Finally, the results are synthesized to reveal the direction of the relationship. It is found that the effect of competitiveness on human development is more significant than the effect of human development on competitiveness. Show more

Keywords: Human development, competitiveness of nations, fuzzy analytic network process, data envelopment analysis

DOI: 10.3233/JIFS-189124

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6629-6643, 2020

Authors: Dursun, Mehtap | Goker, Nazli | Mutlu, Hakan

Article Type: Research Article

Abstract: Organizations make use of project management methodologies, which provide an effective manner to achieve managerial goals, maintain the strength of the companies in increasing competition. Efficiency in planning, budgeting, and scheduling are provided so that high quality outputs are obtained through these processes. Agile project management methodology, which has been emerged from unpredictability of customer requirements and changeable business environment, is apt to cope with the failures of traditional project management tools. Besides, lean six-sigma project management methodology has become a combination of lean and six-sigma, which were opponent methodologies previously. This paper aims to determine the most suitable outsourcing …provider alternative by presenting a novel cognitive maps-based intuitionistic fuzzy decision making procedure. Interrelationships among evaluation criteria are weighted employing intuitionistic fuzzy cognitive map technique because of the causal links among evaluation criteria, vagueness, fuzziness, and hesitation in data. Moreover, the most appropriate provider alternative for both agile and lean six-sigma project management methodologies is identified by utilizing intuitionistic fuzzy TOPSIS method, which aims for minimizing the closeness to the ideal solution while maximizing the distance from the anti-ideal solution in hesitative environment. The case study is carried out in a bank that performs in Turkish banking sector. Show more

Keywords: Intuitionistic fuzzy sets, intuitionistic fuzzy cognitive map, IFTOPSIS, outsourcing provider selection, project management, agile, lean six-sigma

DOI: 10.3233/JIFS-189125

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6645-6655, 2020

Authors: Oner, Mahir | Ustundag, Alp

Article Type: Research Article

Abstract: Since information science and communication technologies had improved significantly, data volumes had expanded. As a result of that situation, advanced pre-processing and analysis of collected data became a crucial topic for extracting meaningful patterns hidden in the data. Therefore, traditional machine learning algorithms generally fail to gather satisfactory results when analyzing complex data. The main reason of this situation is the difficulty of capturing multiple characteristics of the high dimensional data. Within this scope, ensemble learning enables the integration of diversified single models to produce weak predictive results. The final combination is generally achieved by various voting schemes. On the …other hand, if a large amount of single models are utilized, voting mechanism cannot be able to combine these results. At this point, Deep Learning (DL) provides the combination of the ensemble results in a considerable time. Apart from previous studies, we determine various predictive models in order to forecast the outcome of two different case studies. Consequently, data cleaning and feature selection are conducted in advance and three predictive models are defined to be combined. DL based integration is applied substituted for voting mechanism. The weak predictive results are fused based on Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM) using different parameters and datasets and best predictors are extracted. After that, different experimental combinations are evaluated for gathering better prediction results. For comparison, grouped individual results (clusters) with proper parameters are compared with DL based ensemble results. Show more

Keywords: Ensemble learning, deep neural networks, LSTM, deep ensemble learning

DOI: 10.3233/JIFS-189126

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6657-6668, 2020

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6669-6669, 2020

Authors: Barrón-Romero, César | Hernández-Zavala, Antonio

Article Type: Research Article

Abstract: Fuzzy processors are used for control actions in nonlinear mechatronic systems where high processing speed is required. The Field Programmable Gate Arrays (FPGA) are a good option to implement low cost fuzzy hardware in a short development time. A very important block in fuzzy hardware is the fuzzifier, since it affects directly in the accuracy of the result and in the processing time for obtaining a fuzzy number. There have been many design methodologies intended for enhancing the performance of this block. This paper presents a parallel fuzzifier circuit called α -BSSF. Its main design characteristics are the use of …α -levels for membership representation, usage of integer numbers, and avoiding time-consuming operations. As result, we obtained a fuzzifier that shows advantages in the reduction of the response time and computational resources against the existing sequential fuzzification methods. This proposal is targeted not only for T1FS, but also for T2FS, since the membership calculation through fuzzifier is applied in the same way but twice. Show more

Keywords: Digital Circuit design, Fuzzy hardware, Fuzzifier, FPGA, α - levels

DOI: 10.3233/JIFS-190291

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6671-6685, 2020

Authors: Gao, Fei | Zhang, An | Bi, Wenhao

Article Type: Research Article

Abstract: Weapon system operational effectiveness evaluation is of significant importance to weapon system development, and it can be viewed as a multiple criteria decision-making problem with qualitative information, precise data, interval data, and even missing information. Furthermore, due to the complexity of weapon systems and military operations, using prior knowledge such as experiment data, simulation data, and experts’ knowledge could enhance the accuracy and reliability of the evaluation result. To this end, by introducing interval-valued evidential reasoning (ER) approach into belief rule-based system (BRBS), this paper proposed an interval-valued BRB inference method for weapon system operational effectiveness evaluation Firstly, the operational …effectiveness evaluation hierarchy is established based on the analysis of the weapon system. Then, the belief rule base (BRB) is constructed to capture prior knowledge of the weapon system. Next, different kinds of information are transformed into belief distribution, and the proposed interval-valued BRB inference method is applied to relay the input to the BRB and obtain the evaluation result. Finally, three numerical examples of missile system operational effectiveness evaluation with interval data, precise data, and missing information are conducted to illustrate the process of the proposed method and demonstrate its feasibility. Show more

Keywords: Weapon system, operational effectiveness evaluation, belief rule-based system, interval data, evidential reasoning approach

DOI: 10.3233/JIFS-190651

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6687-6701, 2020