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